Analytics India Magazine

India's #1 publisher on Artificial Intelligence, Data Science & Machine Learning

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Which Countries Pay The Most To Data Scientists

Three years back, we published our original research on which countries pay the highest salaries to data scientists. The research was done by collating data science median salaries for major countries, both in absolute dollar terms and Purchasing power parity (PPP) basis. But after almost 3.5 years, how do these salaries stack up now? We decided we will broaden the scope to include 50 major countries and compare the data scientists salaries today. Also read Analytics India Salary Study 2020 Here we plan to uncover the top highest paying countries to data scientist. Here’s how we did it- Extracted salary information for data scientists through the various online portal that included:Job boards like Indeed & monsterCountry specific job boardsSalary research sites like Glassdoor & PayscaleVarious online blogs & discussion forumsFound median salaries for each countryConverted the local currency to dollarsConverted the dollars to PPP relative to US$. Here’s how to read this information: These salaries are not directly reflective of the demand for data scientists in these countries. Salaries in a country are influenced by various factor apart from the demand, like minimum basic salaries, exchange rates & purchasing powerThese are median salaries across all experience levels, industries and skills for data scientists. The goal is to provide a single number across countries that show the parity. We acknowledge the fact that there would be a range of salaries that would be depen Read the full article

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Interview With Kaggle Master Hiroshi Yoshihara

“My ultimate dream is to build a next generation healthcare system with the help of AI technology.” For this week’s ML practitioner’s series, Analytics India Magazine got in touch with Hiroshi Yoshihara, a Kaggle competition master and a machine learning engineer whose work is focussed on public health. He works at Aillis Inc., a Japan based startup developing AI-powered medical devices for early and accurate detection of influenza.  As a machine learning engineer, Hiroshi and his team developed algorithms to process medical images. He is also a full-time doctoral student in public health at Kyoto University. In this interview, Hiroshi shares a few insights from his data science journey. AIM: Can you tell us a bit about the beginning of your data science journey?  Hiroshi: I started learning to program when I was in middle school, and soon I got obsessed with competitive programming. After I entered university, I joined the university team of robot competition as a robot programmer, and also synthetic biology competition as a mathematical modelling engineer. My journey in machine learning started quite unexpectedly. A friend of mine from Russia mistakenly asked me to join an international machine learning competition when I knew almost nothing about machine learning. I was taking a machine learning course at the university, but I could hardly find it interesting until my first participation in the competition.  The first task was a binary classification of particles from Read the full article

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COVID-19: A Data Scientists Contribution In Maintaining Physical Health And Well-being Explained

When we discuss a medical emergency where lakhs of people are in their death bed, and few more lakhs are exposed to the immediate threat, what comes to our mind first is the role of the emergency workers like healthcare professionals, leading the way in this time of crisis. Data Scientists, a white-collar job, with the provision of working from a comfortable set up of home, what can they possibly offer to repair the unprecedented loss of human tribe? Well to answer these let's understand how a data scientist works under the hood. And then let’s look at the role the data scientists can play to ease the effects of COVID-19 pandemic on the well-being of the human tribe. So what’s the illusively elusive term ‘The data science’? The data science is the collective term for data collection, data cleaning, data exploration and modelling. Data can be found in huge size and in many forms and variables, thus making data management complex and a big deal. When we think about large amount of data, statistics is the subject that comes to our mind. So are data scientists basically statistician? The answer would be both Yes and No. Yes, since managing data and fitting it into an efficient model requires an understanding of statistical concepts. A huge area of data science algorithm development covers knowledge about linear algebra and differential calculus. But a statistician may not have knowledge about IDEs and Web scrapping using new-age computing languages like Python and R. So to explain the job profile more clearly, Josh Wills, director of data engineering at Slack said “Person who is better at statistics than any software engineer and better at software engineering than any statistician”. So basically implementing statistics and differential calculus, designing a model using artificial intelligence, machine learning, etc. using programming languages such as Python, R and demonstrating the final model using data visualization tools like Tableau and Power BI is what Data Scientists do, in a nutshell. Now coming to the need of the hour, the COVID 19 pandemic, let’s see how the novel coronavirus is affecting the human race in terms of physical health and well-being and how data science can help ease the situation. The novel coronavirus, which by the time is slowly losing its novelty as the period of contamination is increasing day by day, is highly contagious. Also, there is no possible medicine to cure the disease discovered so far. As the number of people with the disease is increasing, the healthcare facilities are also saturating due to the high volume of patients, leading to a complete collapse of the healthcare system. Social distancing is a way to check the spread, nevertheless, let’s not forget that humans are after all social beings. That is why it is of utmost importance to study the virus for obtaining any possible medication or vaccination.  The challenges are that: a vaccine against a coronavirus was never found before. Also, other coronaviruses such as common cold do not create long-term immunity upon its exposure to the human body. Without the invention of a vaccine, it is nearly impossible to eliminate the virus from the planet. A data scientist can make use of the available genomic data and upon its analysis can provide an understanding of genetic issues and can also help in studying reactions to various kinds of drugs and its effect on diseases. Many types of research involving Generative Adversarial Networks (GAN), a deep learning technique that uses two neural networks, competing against each other in order to generate new synthetic data that can very well replicate real data, is being used to discover the possible drug/vaccine for COVID-19. Google DeepMind had released a dataset of the Protein structure of SARS-CoV-2 which is appreciated for predicting the protein structure of COVID-19 accurately. X-Ray and CT-Scan datasets are also being used to study about many effects of COVID-19 on the human body, Pneumonia being the one. Making use of the demographic data available alongside, AI is used to detect the hotspot zone of infectious disease. Monitoring the availability of hospital resources accounts in dealing with enormous amounts of information. Data science thus comes to rescue, and can be used to keep count of existing essential human resource available like medical professionals, in the vicinity of the zone of interest. Johns Hopkins University, IBM and Tableau, in association with Centers for Disease Control and Prevention (CDC) of US, China and Europe and the World Health Organization (WHO) have released interactive databases that uses real-time graphic information system for viewing details about the patient infected, recovered or died due to this virus. Data Scientists helped in designing a faster way of Contact Tracing, an efficient move to suppress the spread to a large extent. Some contact tracing apps with over a million downloads are India’s Arogya Setu, Singapore’s Trace Together and South Korea’s Corona Watch. These apps by utilizing Bluetooth and GPS technology of the mobile phone sends alerts to users when they breach social distancing norms. If for say, someone comes within close proximity of 10 people during a day, all of them will be enlisted as the person contact chain. In case the nodal man is found to be positive, his contact chain will be intimated through the app and will be insisted to go and get tested. It will also alert the healthcare professional of that area.   The MVP features of these apps are Login credentials, Bluetooth access, self-assessment test, symptom reporter, hotspot locator, affected people details. The efficacy of this idea, however, solely depends upon the rate of downloads. Another app called COVID Symptom Tracker uses machine learning to enable people interact with the app and discuss symptoms and travel history for detecting possible cases. Data scientists are also working to forecast the spread of coronavirus. The machine-learning department of Carnegie Mellon University built a model that processes data from several sources such as flu-related Google searches, Twitter activity, and web traffic to predict the spread of the virus. The data science can be used to study the effect of the virus on some more than others. It can help decide the measures that can help reduce the spread. Data science can also derive an analogy between environmental or genomic factors to the people who are getting advanced respiratory problems. Thus, in conclusion, data science is being used efficiently by new-age data scientists to stabilize the situation and for reshaping the human livelihood. A lot more things still need to be done. Fellow data scientists, are you listening? Read the full article

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Take A Unique Career Path In Blockchain With A Hybrid Program From IIIT Hyderabad & TalentSprint

Blockchain is one of the hottest technologies of this century. From revolutionary uses in the healthcare and finance sectors to niche applications in legal tech, retail and real estate, India is now on its way to becoming one of the biggest blockchain markets in the world. The upward trajectory of this sector can be demonstrated with numbers — Blockchain spend in India has increased at 103.4% during 2018 to reach $154.8 million. Over the forecast period (2019-2025), spend on blockchain is expected to record a CAGR of 47.3%, increasing from $289 million in 2019 to reach $4,348.3 million by 2025. Many companies like Facebook are already implementing blockchain to safeguard the way their users exchange money. Recently, Sanjay Dhotre, Minister of State for Electronics and IT had said earlier this year, “Blockchain technology in India is one of the important research areas having application potential in different domains such as governance, banking and finance, cybersecurity and so on.”

Blockchain Sector Has A Very Prominent Talent Gap In India

From private multinational companies to Central as well as State governments in India, the adoption and implementation of blockchain technology is gaining pace in the country. Earlier this month, Union Minister Ravi Shankar Prasad inaugurated a new Centre of Excellence in Blockchain Technology in Bengaluru. It will facilitate various government departments in their blockchain work, leading to large scale deployment of blockchain applications. But the key question is — with the public and private sector jumping on the blockchain train, is there enough talent to fill this gap? Industry insiders suggest that it is slightly easier to get developers to build applications, but getting persons who have token programming, cryptography and full-stack development knowledge to build applications from scratch is a challenge. In fact, one of the band-aid methods of approaching this problem in India is working with freelancers from Russia and China.

No More Quick-Fix Solutions

Blockchain is now being adopted exponentially across Indian enterprises, irrespective of the size or scale of operation. The demand for blockchain developers was initially hindered by a lack of understanding about the technology and minimal available resources for professionals -- particularly developers -- to learn more about it. However, this scenario is now changing in India with the help of programs and courses which are helping professionals upskill themselves. One of the critically-acclaimed programs in India is by IIIT Hyderabad Blockchain Center of Excellence and TalentSprint which offer the Advanced Certificate Program in Blockchain and Distributed Ledger Technologies. This 18-week program brings participants a hands-on learning experience through IIIT Hyderabad campus visits, weekly live online interactive sessions, hackathons, capstone projects, mentors and an exceptional peer group. With a spotlight on a practitioner-focused syllabus, this program makes sure that the participant masters blockchain beyond cryptocurrency.

The Program

The 18-week course called Advanced Certificate Program in Blockchain, and Distributed Ledger Technologies ensures that the student becomes industry-ready, as the curriculum focusses on escalating a participant from a professional with just a programming background, to a blockchain practitioner. The year 2020 will see the sixth cohort of the program designed by IIIT Hyderabad and TalentSprint. Confidence To Bet On The Knowledge: One of the key strengths of the program is the fact that the students not only become practitioners of blockchain, but they also gain such in-depth knowledge that they can start their ventures. For example, some of the noted names in the startup space like ZeroBlocks, AsliMedicine and PharmBlock have been founded by the program alumni. Sundeep Reddy, Cloud Ops Engineering Specialist and an alumnus says, “By the end of the program, we were confident to build our applications.” Peer-To-Peer Networking: It is a truth universally acknowledged that knowledge could not be limited to textbooks and scripted syllabus. While books and curriculum have a place of great importance in any education, nothing can beat the hands-on experience a student gets from discussing problems and trying to find innovative solutions with peer-to-peer networking. This programme by IIIT-H and TalentSprint has seen classroom peers turned into friends, who then evolved into partners for various ambitious and brilliant projects. Hybrid Format: TalentSprint’s hybrid platform delivers unique onsite and online experiences that help build cutting-edge expertise for the students while ensuring that they are engaged as well as untroubled enough to study. This hybrid format consists of three visits to the IIIT Hyderabad campus, along with living online classes. Career outcomes With an eminent institute like IIIT Hyderabad creating the course structure, this program is bound to be a great solution for any candidate who wants to make a career in blockchain and its allied sectors. This 18-week hands-on program has live online sessions and includes three visits to IIIT Hyderabad, with a focus on crucial topics like: Creating tokensBuilding smart contractsImplementing digital wallets Being able to launch decentralised appsRelated hackathons and capstone projects The program outcome for the participants will include: Expertise in blockchain and distributed ledger technologyHands-on PoC experience across major blockchain platformsExposure to blockchain use cases across domainsAdvanced certification from IIIT-Hyderabad Executive Education  Program at a glance Duration: 18 weeks Course Type: Hybrid format with live online sessions and 3 IIIT-H campus visits Total Fees: ₹2,00,000 + GST Financial Aid: Flexible EMI options available Certification: IIIT Hyderabad Eligibility: Tech Professionals with at least one year of work experience and coding background Read the full article

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Intel Readies For An AI Revolution With A Comprehensive AI Solutions Stack

Global technology player Intel has been a catalyst for some of the most significant technology transformations in the last 50 years, preparing its partners, customers and enterprise users for a digital era. In the area of artificial intelligence (AI) and deep learning (DL), Intel is at the forefront of providing end-to-end solutions that are creating immense business value. But there’s one more area where the technology giant is playing a central role. Intel is going to the heart of the developer community by providing a wealth of software and developer tools that can simplify building and deployment of DL-driven solutions and take care of all computing requirements so that data scientists, machine learning engineers and practitioners can focus on delivering solutions that grant real business value. The company’s software offerings provide a range of options to meet the varying needs of data scientists, developers and researchers at various levels of AI expertise. So, why are AI software development tools more important now than ever? As architectural diversity increases and the compute environment becomes more sophisticated, the developer community needs access to a comprehensive suite of tools that can enable them to build applications better, faster and more easily and reliably without worrying about the underlying architecture. What Intel is primarily doing is empowering coders, data scientists and researchers to become more productive by taking away the code complexity. Intel Makes AI More Accessible For The Developer Community In more ways than one, software has become the last mile between the developers and the underlying hardware infrastructure, enabling them to utilise the optimization capabilities of processors. Analytics India Magazine spoke to Akanksha Bilani, Country Lead – India, Singapore, ANZ at Intel Software to understand why, in today’s world, transformation of software is key to driving effective business, usage models and market opportunity. “Gone are the days where adding more racks to existing platforms helped drive productivity. Moore’s law and AI advocates that the way to take advantage of hardware is by driving innovation on software that runs on top of it. Studies show that modernization, parallelisation and optimization of software on the hardware helps in doubling the performance of our hardware,” she emphasizes. Going forward, the convergence of architecture innovation and optimized software for platforms will be the only way to harness the potential of future paradigms of AI, High Performance Computing (HPC) and the Internet of Everything (IoE). Intel’s Naveen Rao, Corporate Vice President and General Manager, Artificial Intelligence Products Group at Intel Corporation, summed up the above statement at the recently concluded AI Hardware1 summit.  It’s not just a ‘fast chip’ - but a portfolio of products with a software roadmap that can enable the developer community to leverage the capabilities of the new AI hardware. “AI models are growing by 2x every 3 months. So it will take a village of technologies to meet the demands: 2x by software, 2x by architecture, 2x by silicon process and 4x by interconnect,” he stated.  Simplifying AI Workflows With Intel® Software Development Tools As the global technology major leads the way forward in data-driven transformation, we are seeing Intel® Software2 solutions open up a new set of possibilities across multiple sectors. In retail,  the Intel® Distribution of OpenVINO™ Toolkit is helping business leaders3 take advantage of near real-time insights to help make better decisions faster. Wipro4 has built groundbreaking edge AI solutions on server class Intel® Xeon® Scalable Processors and the Intel® Distribution of OpenVINO™ Toolkit. Today, data scientists who are building cutting-edge AI algorithms rely very heavily on Intel® Distribution for Python to get higher performance gains. While stock Python products bring a great deal performance to the table, the Intel performance libraries that come already plugged in with Intel® Distribution for Python help programmes gain more significant speed-ups as compared to the open source scikit-learn. Now, those working in distributed environments leverage BigDL, a DL library for Apache Spark. This distributed DL library helps data scientists accelerate DL inference on CPUs in their Spark environment. “BigDL is an add-on to the machine learning pipeline and delivers an incredible amount of performance gains,” Bilani elaborates.  Then there’s also Intel® Data Analytics Acceleration Library (Intel® DAAL), widely used by data scientists for its range of algorithms, ranging from the most basic descriptive statistics for datasets to more advanced data mining and machine learning algorithms. For every stage in the development pipeline, there are tools providing APIs and it can be used with other popular data platforms such as Hadoop, Matlab, Spark and R. There is also another audience that Intel caters to — the tuning experts who really understand their programs and want to get the maximum performance out of their architecture. For these users, the company offers its Intel Math Kernel Library for Deep Neural Networks (Intel MKL-DNN) — an open source, performance-enhancing library which has been abstracted to a great extent to allow developers to utilise DL frameworks featuring optimized performance on Intel hardware. This platform can accelerate DL frameworks on Intel architecture and developers can also learn more about this tool through tutorials.  The developer community is also excited about yet another ambitious undertaking from Intel, which will soon be out in beta and that truly takes away the complexity brought on by heterogeneous architectures. OneAPI, one of the most ground-breaking multi-year software projects from Intel, offers a single programming methodology across heterogeneous architectures. The end benefit to application developers is that they need no longer maintain separate code bases, multiple programming languages, and different tools and workflows which means that they can now get maximum performance out of their hardware. As Prakash Mallya, Vice President and Managing Director, Sales and Marketing Group, Intel India, explains, “The magic of OneAPI is that it takes away the complexity of the programme and developers can take advantage of the heterogeneity of architectures which implies they can use the architecture that best fits their usage model or use case. It is an ambitious multi-year project and we are committed to working through it every single day to ensure we simplify and not compromise our performance.” According to Bilani, the bottomline of leveraging OneAPI is that it provides an abstracted, unified programming language that actually delivers a one view/OneAPI across all the various architectures. OneAPI will be out in beta in October. How Intel Is Reimagining Computing As architectures get more diverse, Intel is doubling down on a broader roadmap for domain-specific architectures coupled with simplified software tools (libraries and frameworks) that enable abstraction and faster prototyping across its comprehensive AI solutions stack. The company is also scaling adoption of its hardware assets — CPUs, FPGAs, VPUs and the soon to be released Intel Nervana™ Neural Network Processor product line. As Mallya puts it, “Hardware is foundational to our company. We have been building architectures for the last 50 years and we are committed to doing that in the future but if there is one thing I would like to reinforce, it is that in an AI-driven world, as data-centric workloads become more diverse, there’s no single architecture that can fit in.”  That’s why Intel focuses on multiple architectures — whether it is scalar (CPU), vector (GPU), matrix (AI) or spatial (FPGA). The Intel team is working towards offering more synchrony between all the hardware layers and software. For example, Intel Xeon Scalable processors have undergone generational improvements and are now seeing a drift towards instructions which are very specific to AI.  Vector Neural Network Instruction (VNNI), built into the 2nd Generation Intel Xeon Scalable processors, delivers enhanced AI performance. Advanced Vector Extensions (AVX), on the other hand, are instructions that have already been a part of Intel Xeon technology for the last five years. While AVX allows engineers to get the performance they need on a Xeon processor, VNNI enables data scientists and machine learning engineers to maximize AI performance. Here’s where Intel is upping the game in terms of heterogeneity — from generic CPUs (2nd Gen Intel Xeon Scalable processors) running specific instructions for AI to actually having a complete product built for both training and inference. Earlier in August at the Hot Chips 2019, Intel announced the Intel Nervana Neural Network processors4, designed from the ground up to run full AI workloads that cannot run on GPUs which are more general purpose. The Bottomline: a) Deploy AI anywhere with unprecedented hardware choice  b) Software capabilities that sit on top of hardware  c) Enriching community support to get up to speed with the latest tools  Winning the AI Race For Intel, the winning factor has been staying closely aligned with its strategy of ‘no one size fits all’ approach and ensuring its evolving portfolio of solutions and products stays AI-relevant. The technology behemoth has been at the forefront of the AI revolution, helping enterprises and startups operationalize AI by reimagining computing and offering full-stack AI solutions, spanning software and hardware that add additional value to end customers. Intel has also heavily built up a complete ecosystem of partnerships and has made significant inroads into specific industry verticals and applications like telecom, healthcare and retail, helping the company drive long-term growth. As Mallya sums up, the way forward is through meaningful collaborations and making the vision of AI for India a reality using powerful best-in-class tools.  Sources 1AI Hardware Summit: https://twitter.com/karlfreund 2Intel Software Solutions: https://software.intel.com/en-us 3Accelerate Vision Anywhere With OpenVINO™ Toolkit: https://www.intel.in/content/www/in/en/internet-of-things/openvino-toolkit.html 4At Hot Chips, Intel Pushes ‘AI Everywhere’: https://newsroom.intel.com/news/hot-chips-2019/#gs.8w7pme Read the full article

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Report: Indian AI Startup Funding in 2019

AIMResearch presents the impactful insights on the funding of AI startups in India.  The booming Data Science space in India continues to attract the attention of Venture Capital and Investor funds – thus highlighting the potential of the Indian Data Science market. After attracting close to $530 Mn in investment in 2018, the Indian AI startup market continued to be the focus of leading global funds, receiving $762.5 Mn funding in 2019. This comprehensive report studies the funding trends of AI and Analytics startups in 2019. It provides wide-ranging insights including the concentration of start-ups by geography, the spread and focus by data science domains, and startups that brought in the largest investments. The report covers the types of investment firms backing startups – covering details on the stage(s) of funding, number of investors, and lead investor(s) across the big-ticket funding. The report goes one step further in evaluating the funding received for undisclosed investment rounds– this evaluation was performed on the basis of several distinct criteria including, the valuation and revenues of the specific startup, and the typical investments by carried out by funds in other startups of similar size, capability, and potential. Read last year's report, here. Overview The Indian AI and Analytics startups continued to attract investment in 2019, receiving $762.5 Mn in funding, a 44% increase over the $530 Mn funding received in 2018. This steady growth in funding seems insignificant compared with the 368% growth from 2017 and 2018.

However, this does not signify a slowdown in the startup investment climate. Instead, it indicates a stable and maturing Indian analytics market, in which companies that satisfy a critical market need for Analytics and AI services continue to attract global investments and interest. The data in our report covers startups that received funds at various stages of development – from early-stage to growth /expansion stage enterprises, and this was reflected by the rounds of funding that varied from Seed to Series A/B/C/D to Late-Stage Private equity. Mumbai-based Fractal Analytics, which brings Analytics and Artificial Intelligence to various phases of enterprise decision-making, raised the largest amount in funding, receiving $200 Million in a private equity (PE) round from Apax partners, a PE firm. The deal was in exchange for 45% stake in Fractal, with Apax buying out the analytics firm’s investors. The funding data indicates that funds invested in startups focused not just on general Data Science domains, covering Artificial Intelligence, Machine Learning, and Analytics, but also on niche domains, including Natural Language Processing NLP, Robotics, and Computer Vision. Correspondingly the industries serviced by these startups covered wide spectrum of sectors, including Agriculture, Healthcare & Diagnostics, Financial Services, Supply Chain & Logistics, Retail, and Industrial, among others. This indicates a strengthening of the state of the Data Science startup environment, symbolizing future stable growth and investments. Read the complete report, here. Read the full article

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Data Freedom- The Path To Unlocking True Enterprise Intelligence

Today, companies across the globe are redefining their business models and seeking innovative ways to extract data, connect it and employ it for meaningful insights and learning. But for any enterprise to become intelligent, they should have the freedom to efficiently utilise all data they are creating and consuming to make smarter business decisions. The smart insights have to be entirely driven by data, not human judgement, or assumptions. This is precisely where the philosophy of Data Freedom comes in.  The concept of Data Freedom is about good-quality data being available within the enterprise in good quality, on an agile platform to all operational users. This includes IT and DevOps, analytical users like data scientists, decision-makers like business executives, and external users who are part of the business value chain. Data Freedom is also about how enterprises can innovate the data state of an organisation as a whole, all the way from data processing to overall data management to align with the digital disruption. For instance, if sensor data is coming from IoT devices, organisations have to be on the lookout for how they can perform real-time processing and make insights available on the fly.  Data Freedom First Requires Data Transformation One of the main aspects of achieving Data Freedom is the transformation of data itself as part of building an intelligent enterprise. When we look into data transformation, we are looking into two strategies- defensive and offensive. The defensive strategy deals with standardising data, optimising it and making it more secure whether it is data processing, data management or data storage.  On the other hand, the offensive strategy of data transformation deals with innovation and monetisation of the data. The following example can elaborate on this. Wipro- one of the leading IT services providers in the world- helped in overall savings of AUD 28M annually for a leading consumer electronics manufacturer by building a unified, scalable consumption platform. The platform which Wipro created helped in achieving effective marketing campaigns, churn and fraud management. This shows that if a data platform is available to all users in the enterprise, it can reap in significant benefits in cost and innovation. Cloud Is At The Heart Of Data Freedom Cloud has become the leading enabler of Data Freedom. No wonder, the worldwide public cloud services market is projected to grow 17.5 % in 2019 to massive $214.3 billion, up from $182.4 billion in 2018, according to Gartner. The fastest-growing market segment here is cloud system infrastructure services or infrastructure as a service (IaaS).  Cloud platforms make storage and processing capability accessible and impactful for all business users in a highly cost optimised manner as compared to on-prem infrastructure. Cloud also makes innovation a level-playing field for all tech companies and empower an entire ecosystem of SaaS startups which are available on the cloud. According to experts, the freedom of business customisation like upscaling, downscaling, server-less cannot be accomplished without utilising the flexibility of the cloud. For democratisation and monetisation of data, cloud, therefore, becomes key. Unless enterprises leverage cloud, their services may not be to perform massive-scale and complex computing needed for Industry 4.0 services. Cloud also becomes a cost factor plus capability factor to power Data Freedom.  Creating A Cloud-Native Architecture According to experts, the first step is to make systems cloud-enabled through migration. Once a business migrates, then the second approach is to make the business cloud-centric, which is around putting data on the cloud. Migration and making the organisation cloud-centric includes looking into data stores, whether it is transactional data, operational data or analytical data.  Businesses also have documents, weblogs and a bunch of file stores for various reporting and policy verifications. So, what companies need is factoring the ETL pipeline and refactor data consumption from all business processes. Data could be anywhere in structured databases or unstructured databases, in-memory databases, columnar databases, graph database, traditional, NoSQL databases, big data ecosystems, etc. Finally, an effective cloud strategy entails innovating by creating a complete cloud-native architecture for Data Freedom. Here, it’s about working with big cloud service providers to utilise the best of the capability on data processing and insight generation on the unified cloud platform.  Achieving AI Infusion At Scale There is more data generated in the last two years than the complete history of human civilisation, and this is leading to fast-evolving AI innovation where enterprises creating profound capacities dependent on data that they possess. In any case, the difficulties with respect to scalability and adoption perpetually hamper enterprise journey towards becoming an AI-infused organisation. To build, AI-powered transformation, is it just about the right technology tools or is there something which is substantially more noteworthy in play?   The need for businesses is to have intelligent systems which can assist them with accomplishing AI infusion at scale— something which is incredibly challenging to achieve. Digging deep, we can find that there are only a handful of solutions that exist in the market, which can infuse AI efficiently across the complex business value chains.  One such example is Wipro’s Intelligent Data Platform which delivers an infusion of AI/ML with all the data at speed and scale for faster and intelligent insights through its Next-Gen Data Warehouse and Data Lake. Cloud Data Pods, a cloud-agnostic studio powered by Wipro’s solutions and IP also provides best-in-class customer experiences in delivering entire value chain of data to decision. Such solutions can add tremendous value by leveraging data transformation and infusing analytics in each process of a business unit.  Conclusion The road to Data Freedom is enabling such a unified platform on the cloud where business users can search all the attributes with centralised enterprise search capability. This entails that all enterprises moving into a scalable, highly flexible and common platform to provide a free environment without data security constraints. With all the data on one cloud platform, it’s time to leverage the power of advanced analytics and AI.  Read the full article

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Report: Indian AI Startup Funding in 2019

AIMResearch presents the impactful insights on the funding of AI startups in India.  The booming Data Science space in India continues to attract the attention of Venture Capital and Investor funds – thus highlighting the potential of the Indian Data Science market. After attracting close to $530 Mn in investment in 2018, the Indian AI startup market continued to be the focus of leading global funds, receiving $762.5 Mn funding in 2019. This comprehensive report studies the funding trends of AI and Analytics startups in 2019. It provides wide-ranging insights including the concentration of start-ups by geography, the spread and focus by data science domains, and startups that brought in the largest investments. The report covers the types of investment firms backing startups – covering details on the stage(s) of funding, number of investors, and lead investor(s) across the big-ticket funding. The report goes one step further in evaluating the funding received for undisclosed investment rounds– this evaluation was performed on the basis of several distinct criteria including, the valuation and revenues of the specific startup, and the typical investments by carried out by funds in other startups of similar size, capability, and potential. Read last year's report, here. Overview The Indian AI and Analytics startups continued to attract investment in 2019, receiving $762.5 Mn in funding, a 44% increase over the $530 Mn funding received in 2018. This steady growth in funding seems insignificant compared with the 368% growth from 2017 and 2018.

However, this does not signify a slowdown in the startup investment climate. Instead, it indicates a stable and maturing Indian analytics market, in which companies that satisfy a critical market need for Analytics and AI services continue to attract global investments and interest. The data in our report covers startups that received funds at various stages of development – from early-stage to growth /expansion stage enterprises, and this was reflected by the rounds of funding that varied from Seed to Series A/B/C/D to Late-Stage Private equity. Mumbai-based Fractal Analytics, which brings Analytics and Artificial Intelligence to various phases of enterprise decision-making, raised the largest amount in funding, receiving $200 Million in a private equity (PE) round from Apax partners, a PE firm. The deal was in exchange for 45% stake in Fractal, with Apax buying out the analytics firm’s investors. The funding data indicates that funds invested in startups focused not just on general Data Science domains, covering Artificial Intelligence, Machine Learning, and Analytics, but also on niche domains, including Natural Language Processing NLP, Robotics, and Computer Vision. Correspondingly the industries serviced by these startups covered wide spectrum of sectors, including Agriculture, Healthcare & Diagnostics, Financial Services, Supply Chain & Logistics, Retail, and Industrial, among others. This indicates a strengthening of the state of the Data Science startup environment, symbolizing future stable growth and investments. Read the complete report, here. Read the full article

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Intel Powers AI At The Edge With Intel® Neural Compute Stick 2

Intel Neural Compute Stick 2 is an end-to-end platform for bringing AI prototypes to market in a cost-effective way. Today, much of Artificial Intelligence (AI) training and inference happens in the cloud or in data centers, which requires tremendous compute and processing power. Now, with the world moving to the edge, what if you can get a deep learning processor on a USB stick that supports demanding workloads at low power? Intel® Neural Compute Stick 2 (Intel NCS 2), a USB-based kit brings the power of AI algorithms to the edge and helps in the development and deployment of AI systems for data scientists and developers. Intel NCS 2 is an end-to-end platform for bringing AI prototypes to market in a cost-effective way. It is one of the best hardware alternatives to cloud-based platforms and ideal for vision-based applications, especially image recognition, identification and classification tasks. Developers and data scientists can use it to test as well as deploy deep neural networks and computer vision applications in augmented reality (AR) and Internet of Things (IoT) devices, drones, robotics and smart cameras. In this informative infographic, check out how to set up Intel NCS 2 and get started with your first computer vision application. Read the full article

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Reskilling At Scale: How To Prepare For The Age Of Artificial Intelligence?

Taking inspiration from organisations like Wipro, it is the need of the hour to urge the workforce to focus reskilling, secure learning tools and create customised learning plans.  Artificial intelligence is set to disrupt the job market for all types of industries, changing the way we run our operations, businesses, and dealing with existing or new customers. New kinds of workers will be fundamental, working along with robots and increasing automation to drive company-wide AI strategies. However, it is also true that many companies and employees may not be prepared for AI advancements and significant cultural change.  Even as it causes declines in some jobs, automation will change much more. Research says that in about 60% of jobs, at least 30% of the job activities could be automated, which highlights substantial workplace transformations and changes for all future workers. As a result, modern organisations need to accomplish more in arranging for the upcoming employment disruption, and how workers need to get ready for the automation age.  The preparation is crucial because AI is estimated to impact workers at all skills and training levels, and the first target will be to get rid of repetitive functions and then move towards augmented intelligence that enhances the human brain. The influence can be understood from the fact that global organisations such as the World Economic Forum and International Labour Organisation have defined policies to prepare for the AI disruption. As a result, experts do not doubt that AI will uproot a few job roles, and make new types of jobs in light of the movements in profitability and client requirements. On the other hand, it will also bring ground-breaking new tools for the workforce that can enhance efficiency at different levels. Businesses are, therefore comprehending retraining workers to address foreseen interruption in the job market. There is also a quickly expanding interest for hybrid-type job functions which implies that understanding the nature of neighbouring abilities and the market interest for these aptitudes, as opposed to one particular job has also created pathways to new doors utilising reskilling. For instance, as the value of deriving insights from data has increased dramatically, more jobs require data science and AI abilities in addition to other technology aptitudes. This holds for all departments in the company, whether it is sales, marketing or IT, AI skills are needed across the board.  Why Continuous Learning Via Training Programs Becomes Crucial According to experts, there are some necessary skills which data scientists should learn for AI/ML projects. These include programming languages such as Python and R along with fundamentals of Statistics and Machine Learning concepts to help leverage various open-source libraries, ML engines and Cognitive APIs across different platforms. Then, to take it to the next level, one needs to do advanced things like understanding various ML algorithms, creating Neural Networks and Deep Learning models and finally do model testing and hyperparameter tuning. All of this requires extensive training, for which most companies may not be prepared at the moment. Yet, there are some organisations which are working to ensure that skills gaps are addressed through constant learning and engagement with employees. For example, at Wipro runs multiple such initiatives which are aimed at reskilling required for the AI age. With the internal training hub-School of Decision Sciences and Cloud environments like Top Gear, Wipro has made learning an engaging and fun process for its vast staff base. For AI and machine learning, the organisation has designed courses at various levels.  To understand the implications of AI and automation on both technical and non-technical jobs, Analytics India Magazine got in touch with Ramswaroop Mishra, who has taken the initiative of reskilling and preparing over a lakh employees across Wipro and shed light on the numerous initiatives his organisation has undertaken to push reskilling for on a mega scale.  "Our training initiatives are customised in such a way because different jobs will have different needs for reskilling. For technical jobs, we have defined the various levels. At level one, we have application developers, level two is for Applied AI & ML Engineers and at level three we are building our core AI & ML engineers. For each of these levels, we have defined our own courses,” told Ramswaroop Mishra, Data, Analytics and AI Competency Head at Wipro. For building advanced data skills, Wipro’s School of Decision Sciences serves as an online platform where employees can register for different courses in areas of AI and data science which employees take up and learn at their own pace and interest. Apart from that, Wipro’s internal crowdsourcing platform TopGear gives assignments and activities which are accessible for learners to get hands-on involvement with real projects of the company. Wipro’s reskilling initiatives do not just stop there-- the organisation also has collaborated with industry body Nasscom for initiatives like FutureSkills-TalentNext program which aims to train 10,000 students from 30 engineering colleges in India on advanced technology skills.  Experts like Ramswaroop Mishra say that future learning will be focused on a platform-based approach which helps to learn the skills needed for emerging technologies. More importantly, online platforms help individuals develop an aptitude for learning as it allows content and people to come together. On the other hand, with so much content available today, curating the best content for future jobs, or specific enterprise needs remains a challenging task for most companies.  The Need Of The Hour  To get ready for AI impact, organisations need to comprehend the present training scenario, its restrictions, look at the most recent research on the future abilities and feature the best business, HR systems and instructive models. With cooperation particularly across public and private associations, business leaders can create viable skills coordinating across tech solutions, deep-rooted learning and reskilling to deal with the changing universe of work.  Be it Full-Stack, DevOps, Micro Services, IoT, Big Data, data science or machine learning, companies have to carefully examine and drive various training initiatives through devices and platforms for hands-on reskilling for employees. Taking inspiration from organisations like Wipro, it is the need of the hour to urge the workforce to focus reskilling, secure learning tools and create customised learning plans.  Read the full article

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AI & Machine Learning Learning Path: A Definitive Guide

Artificial intelligence is currently one of the hottest buzzwords in tech — with good reason. In the last few years, we have seen several technologies previously in the realm of science fiction transform into reality. Experts look at artificial intelligence as a factor of production, that has the potential to introduce new sources of growth and change the way work is done across industries. In fact, AI technologies could increase labour productivity by 40% or more by 2035, according to a recent report by Accenture. This could double economic growth in 12 developed nations that continue to draw talented and experienced professionals to work in this field. According to Gartner's 2019 CIO Agenda survey, the percentage of organizations adopting AI jumped from four to 14% between 2018 and 2019. Given the benefits that AI and machine learning (ML) enable in business analysis, risk assessment, and R&D — and, the resulting cost-savings — AI implementation will continue to rise in 2020. However, many organizations that adopt AI and machine learning don’t fully understand these technologies. In fact, Forbes points out that 40% of the European companies claiming to be ‘AI startups’ don’t use the technology at all. While the benefits of AI and ML are becoming more evident, businesses need to step up and hire people with the right skills to implement these technologies. Some are well on their way. KPMG’s recent survey of Global 500 companies shows that most of those surveyed expect their investment in AI-related talent to increase by 50 to 100% over the next three years.

Why Pursue AI and Machine Learning Courses?

As data science and AI industries continue to expand, more people are beginning to understand just how valuable it is to have a qualified AI Engineer or data scientist on their team. As a matter of fact, Indeed.com revealed that job postings for data scientists and AI rose over 29% between May 2018 and May 2019. Many people who want to get into this field, typically start with YouTube videos or other free online courses. This approach is definitely good to get your feet wet, but you can't make a career jump based on these alone. What you need is to get a handle on the fundamentals of data science is experience through hands-on projects, where you get guidance from experts. These opportunities are not generally available in the workplace, especially if your current role does not involve data science. However, there are some excellent, comprehensive courses that you can enrol in, which will provide you with all of the above. Courses like Simplilearn's Artificial Intelligence Engineer program enable you to learn, practice, and interact with expert instructors and peer, in live, online sessions. You don't even have to travel.  If you’re looking for a course that keeps students up to date on the latest trends in AI and machine learning through practical projects and industry expert-led instruction, Simplilearn’s AI Engineer and Machine Learning Certification courses are excellent options. There is no better time than now to get started, especially if you want to get ahead of your peers.

Learning Path: How to Get an AI and Machine Learning Career Started

Choosing a learning path for AI and machine learning training can be overwhelming due to all the options out there, but it’s ideal to choose a program that best suits your needs and goals. Successful data scientists usually have a thorough comprehension of various tools and programming languages. They also understand what their roles are in the grand scheme of things. With these skills, you can easily stand out from the competition with potential employers. Some of the programming languages include SAS, R, and Python. What you’ll need to know depends on different variables, such as the specific project you’re working on or the company you’re working for. In order to be a well-rounded candidate that can take on any type of project, it’s critical to know all three of these programming languages. Beyond that, it’s also helpful for data scientists to learn about AI and machine learning. When you enrol in an accredited data science learning program, you’ll get comprehensive training in the field. Let’s dig into some suggested learning paths for AI and machine learning to give you a better idea of what’s available and what to expect.

Artificial Intelligence Engineer Master’s Program

Simplilearn’s Artificial Intelligence Master’s Program, co-developed with IBM, is a blend of artificial intelligence, data science, machine learning, and deep learning — facilitating the real-world implementation of advanced tools and techniques. The program is designed to give you in-depth knowledge of AI concepts including the essentials of statistics (required for data science), Python programming, and machine learning. Through these courses, you will learn how to use Python libraries like NumPY, SciPy, Scikit; as well as essential machine learning techniques, such as supervised and unsupervised learning, advanced concepts covering artificial neural networks, layers of data abstraction, and the basics of TensorFlow. Next, let’s look at the courses that are included in this program, which can also be taken separately. Data Science with Python The Data Science with Python course provides students with all-around data science instruction that includes data visualization, machine learning, data analysis, and natural language processing using Python. As a data scientist, it’s crucial to add Python to your skillset, as more and more professionals in the industry are mastering this programming language. In fact, it has been reported that with seven million people now using Python, surpassing Java as the top programing language. This course is not only suited for those wishing to pursue a career as a data scientist but can also be beneficial for anyone looking to work in data analytics or software development. Machine Learning As a data scientist, mastering machine learning is often a requirement, and the best way to do so is by enrolling in an accredited learning program and earning a machine learning certification. Although there are free online learning sources and tutorials, such as blogs and YouTube videos, these unstructured learning methods don’t always cover all aspects of ML. Also, self-learners may not be able to stay up-to-date on industry changes or receive certifications. Through our machine learning course, students are introduced to various techniques and concepts, such as mathematical and heuristic aspects, supervised and unsupervised learning, algorithm development, and hands-on modelling. This course is ideal for those who want to add to their skill set as a data scientist, or for those who wish to pursue a career as a machine learning engineer. Deep Learning with TensorFlow Deep learning is one of the most exciting and promising segments of artificial intelligence and machine learning technologies. Our Deep Learning with TensorFlow and Keras course is designed to help you master key deep learning techniques. You’ll learn how to build deep learning models using TensorFlow, the open-source software library developed by Google to conduct machine learning and deep neural networks research. It is one of the most popular software platforms used for deep learning and contains powerful tools to help you build and implement artificial neural networks. Advancements in deep learning are already showing up in smartphone applications and efficient power grids. The technology is also driving innovations in healthcare, improving agricultural yields, and helping us find solutions to climate change. With this Tensorflow course, you’ll build expertise in deep learning models, learn to operate TensorFlow to manage neural networks, and how to interpret the results. Natural Language Processing (NLP) Simplilearn’s NLP course gives you a detailed look at the science of applying machine learning algorithms to process large amounts of natural language data. You will learn the concepts of statistical machine translation and neural models, deep semantic similarity models (DSSM), neural knowledge base embedding, deep reinforcement learning techniques, neural models applied in image captioning, and visual question answering using Python’s Natural Language Toolkit (NLTK). AI Capstone Project Simplilearn’s Artificial Intelligence (AI) Capstone project gives you the opportunity to implement the skills you learned in the AI Engineer Master’s program. With dedicated mentoring sessions, you’ll learn how to solve a real industry problem. You'll also learn various AI-based supervised and unsupervised techniques like regression, multinomial Naïve Bayes, SVM, tree-based algorithms, NLP, etc. The project is the final step in the learning path and will help you to showcase your expertise to potential employers.

Bottom Line

There is no denying that the job market is competitive. In fact, the Bureau of Labor Statistics recently released a report that reveals how the job market is tightening. If you’re looking for a stable industry that isn’t going anywhere anytime soon, AI and machine learning are excellent choices. However, choosing a growing and successful industry is only half the battle when it comes to job security. There is also a competition to consider — oftentimes, many qualified candidates are vying for the same job opening. One of the best ways to ensure you stand out to recruiters and employers is to have the right credentials. Earning your certifications in AI and machine learning, or other relevant fields is a surefire way to get your resume noticed by the right people. Get started today! Read the full article

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Developers Heads Up: Register For Data Engineering Workshop By Google Cloud, Qubole & AIM

Analytics India Magazine in collaboration with Google Cloud and Qubole is organising a workshop for developers who work extensively on data analytics platforms. This is a huge opportunity for the developers and data engineers who are looking to gain hands-on experience on how to leverage Google Cloud Platform and build end-to-end solutions. This workshop will be held in Mumbai on 25 January and in Gurugram on 1 February. Click here to Register. Mumbai venue:

Gurugram venue:

If selected, participants will receive a confirmation email stating the same. Only selected participants will be allowed to enter the premise of the workshop. Direct walk-in OR on the day OR on the spot registrations will not be permitted at all.  The last day for registration is: 24th January 2020, 11 AM for Mumbai Workshop and, 31st January 2020, 11 AM or Gurugram Workshop.

Workshop Details At A Glance 10:00 AM - 10:30 AM Registration 10:30 AM - 11:00 AM Workshop Begins Intros and Workshop Overview 11:00 AM - 12:30 PM Hands-On session on building pipelines for ML 12:30 PM - 1:00 PM Q&A Session                    1:00 PM Network + Lunch Register for the workshop here. Who Should Attend This Workshop? This workshop will benefit those participants who: want to learn to acquire and transform data sets for data science and analytics want to learn how to make data sets available to different users and fully leverage a GCP data lake throughout your organizationwant access to a pre-configured Qubole environment that will be loaded with datasets and the appropriate tools, including Apache Spark and Airflow, as well as interactive notebookswant to build an end-to-end solution that addresses common business scenarios Tools And Techniques That Will Be Used The participants will get their hands on the following tools and techniques at the workshop: Create Metadata on Data MetastoreDDLs Transformation/Cleaning/Denormalization Hive/Spark JobsAirflow/SchedulerBigQuery IntegrationREST APIs Data Analysis Demonstrate using examples: Autoscaling and Preemptive VMsPresto queriesQu Workbench Notebooks Demo ZeppelinPackage Management Key Takeaways By the end of this workshop, the participants are expected to know about: Ingesting the data to and from Google Cloud Storage (GCS) data lake.Performing interactive data analysis and building AI/ML models using Spark or custom python packages.Transforming the data set with Spark and building interactive dashboards.Seamlessly interacting with other data sources like BigQuery through SQL Workbench.Deploying end-to-end data pipeline using Apache Airflow. Register for the workshop here. Read the full article

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Top 10 Cybersecurity Courses In India: Ranking 2020

Indian enterprises — be it larger companies or smaller enterprises — are always on the hunt for skilled cybersecurity professionals to augment their digital infrastructure and safeguard their data from unwanted intrusions. Although there are several job vacancies in the country, recruiters are still facing a big challenge to find the right resources for the positions.  According to a report, the increasing cyber-attacks and data protection laws are expected to create 1 million jobs and $35 billion opportunities for India by 2025. So, this could be an opportunity for individuals interested in cybersecurity as a career option.  As the country is creating massive opportunities, enterprises are desperate to hire people for a lucrative pay scale; however, a significant amount of upskilling is required. Here’s our first-ever ranking of Cybersecurity courses in India. A primary survey which was conducted a few months back was taken into consideration to understand the preferences of candidates, based on their experience. The survey helped to invalidate the data and providing a rationale for the ranking, wherever required. Students feedback and expert advice were also accounted for the overall ranking process. The courses that have not been mentioned in the ranking either did not participate or did not make it to the top ten.  1. Master Certificate in Cyber Security (Red Team) - Jigsaw Academy

Jigsaw Academy is an award-winning online analytics and big data training provider headquartered in Bengaluru, India. Founded by the duo of Gaurav Vohra and Sarita Digumarti, Jigsaw Academy has been instrumental in shaping the careers of over 50,000 learners in 30+ countries by helping them build a successful career in emerging technologies with specialised industry oriented courses. Jigsaw Academy trains professionals in the areas of analytics, data science, big data, machine learning, business analytics, and more recently, cyber security and cloud computing.  Flagship Cybersecurity Program: Jigsaw Academy’s Master Certificate in Cyber Security (Red Team) Duration Of The Program: 600 Hours (20 Hours of Live Online Instructor-Led, and 40 Hours of In-person Classroom - Basic and Fundamental Program + 4 Months-Main Program) Cost Of The Program: ₹2,80,000 + Taxes (Scholarships available up to ₹70,000) Cities Of Operation: Bengaluru Course Content And USP Of The Program: Jigsaw Academy’s Master Certificate in Cyber Security (Red Team), is the only program on offensive technology in India. The program is intensive in delivery and extensive in technology coverage and is delivered in collaboration with/by HackerU, Israel’s premier cybersecurity training institute. HackerU has more than 20 years of experience in providing cybersecurity solutions and training in the US, Singapore, Russia, Australia, and other geographies in the US and European market. The course covers more than 14 modules in 3 different phases focusing on network fundamentals, Windows, Linux Administration, applicative hacking and penetration testing on emerging technologies like IoT.  2. Stanford Advanced Computer Security Program - Great Learning

Great Learning is a technology-enabled online and blended-model learning organization that offers high-quality, impactful and industry-relevant learning programs to working professionals. The programs help learners master ‘hard’ competencies such as business analytics, data science, big data, machine learning, artificial intelligence, cloud computing, cybersecurity, digital marketing and digital business. Great Learning’s analytics programs have been ranked #1 in India for five years in a row, and its professional learning programs have delivered over 6 million hours of impactful learning to over 10,000 learners. Flagship Cybersecurity Program: Stanford Advanced Computer Security Program Duration Of The Program: 6 Months Cost Of The Program: $2,495 or ₹1,74,650 (approximately) Cities Of Operation: Online for India, UK, South East Asia, Australia and other international locations Course Content And USP Of The Program: Advanced Computer Security Program is created by Stanford University, and is taught by distinguished faculty from Stanford’s Computer Science and Engineering departments. The comprehensive program covers all the essential areas in cybersecurity from a practitioner’s perspective. Some of the salient features of the program are: A certificate of achievement from Stanford EngineeringRegular mentorship from industry experts in cybersecurityHands-on practice through a series of labs and projects that allows participants to put what they learned to practice. This program is aimed at aspiring security and system architects and provides a holistic understanding of the various moving parts within cybersecurity. The range of topics covered in the program includes web applications security, network security, mobile security, cryptography, writing secure code, and other emerging threats and defences.  3. PGP in Cybersecurity - Praxis Business School

Praxis Business School is committed to playing a significant role in creating a strong pool of resources who understand the interplay among data, technology and business and can contribute significantly to the exciting Digital Future. Praxis is well known for the quality of the faculty team that it has been able to build. Faculty members with impeccable academic pedigree and enormous industry experience design and deliver programs that are relevant and effective. Thus, Praxis programs have been well received by the industry and the Data Science program has been consistently ranked as one of the top 3 programs in data science in India by prominent publications. Flagship Cybersecurity Program: PGP in Cybersecurity  Duration Of The Program: 9 months and 525 Hours (It does not include self-study, group discussion, R&D, practice, seminar/workshop, etc.) Cost of the program: ₹3,00,000 Cities of Operation: Kolkata, India Course Content And USP Of The Program: On successful completion of the course, the students will learn how to detect a cyber attack and respond during an attacked scenario, identify, assess and mitigate cyber risk, assess the cybersecurity posture of the any enterprise, find technical vulnerabilities of any ICT infrastructure, be a strategist in cybersecurity roadmap creation, identify legal, regulatory and statutory requirements impacting cybersecurity, build a cyber safe IT and OT (Operation Technology) environment, become a digital forensics investigator, conduct cybersecurity audit, and become a compliance manager. All the programs can be done by any individual who has completed their graduation (both three years and four years duration) in engineering, science or any other stream and wants to pursue his/her career in the field of cybersecurity.  4. Certified Ethical Hacker and Certified Information System Security Professional - Simplilearn

Simplilearn enables professionals and enterprises to succeed in this fast-changing digital economy. The company provides outcome-based online training across digital technologies and applications such as big data, machine learning, AI, cloud computing, cybersecurity, digital marketing and other emerging technologies. Based out of San Francisco, CA, Raleigh, NC and Bengaluru, India, Simplilearn has helped more than one million professionals and 1,000 companies across 150 countries in getting trained, acquiring certifications, and reaching their business and career goals. The training industry-recognized Simplilearn as a Top 20 IT Training Company for 2017-2019. Flagship Cybersecurity Program: Certified Ethical Hacker (CEH), and Certified Information System Security Professional (CISSP) Duration Of The Program: 40 hrs for CEH program, and 32 hrs for CISSP program Cost Of The Program: ₹35,999 for CEH and ₹24,999 for CISSP. Cities Of Operation: Bengaluru, Hyderabad, Pune, Mumbai, Gurugram, Noida, Singapore and the US Course Content And USP Of The Program: The EC-Council Certified Ethical Hacker course verifies your advanced security skill-sets to thrive in the worldwide information security domain. Many IT departments have made CEH certification a compulsory qualification for security-related posts, making it a go-to certification for security professionals. This certification provides learners with the tools and techniques used by hackers and information security professionals alike to break into any computer system. This course will immerse the learner into a "hacker mindset" to teach how to think like a hacker, and better defend against future attacks. It also offers a hands-on training environment employing a systematic ethical hacking process. The course covers five phases of ethical hacking, diving into reconnaissance, gaining access, enumeration, maintaining access, and covering your tracks. Simplilearn's CISSP certification training is aligned to the (ISC)² CBK latest requirements. The course trains you in the industry's most recent best practices which will help you pass the exam in the first attempt. The certification helps you develop expertise in defining the architecture and in designing, building, and maintaining a secure business environment for your organization using globally approved Information Security standards. 5. PG Diploma/M.Tech in Cybersecurity - Reva University

REVA Academy for Corporate Excellence (RACE), is an initiative of REVA University, which offers a range of specialised, techno-functional programs in emerging technology areas, custom-designed to suit the needs of working professionals to enhance their careers. These programs bring in the latest tools, techniques and skill sets which are in sync with the futuristic demands of the industry. All our programs have a blended learning model with flexible contact classes and a robust online learning management system with 24/7 support. Flagship Cybersecurity program: PG Diploma/M.Tech in Cybersecurity (Powered by AforeCybersec and in association with IBM). Duration Of The Program: 12 months PG Diploma and 24 months M.Tech Program Cost of the program: 12 months PG Diploma is ₹3,50,000 and 24 months M Tech program in ₹4,50,000 lakhs. Cities Of Operation: Bengaluru Course content and USP of the program: PG Diploma/M. Tech in cybersecurity is a 12/24 months program in cybersecurity for working professionals that provides in-depth knowledge and skillsets in cybersecurity to monitor, prepare, predict, detect and respond to cyber-attacks and manage enterprise security. This program is designed and delivered by industry experts. It focuses on providing in-depth knowledge and skills on information security, application security, cloud security, identity and access management, vulnerability and penetration testing, incident management, and SOC operations. This program extensively runs on the virtual environment provided by Cyber Range incorporating hyper-realistic emulators, including traffic generators. To enhance the real-time learning, a state-of-the-art, futuristic Security Operations Centre is built at REVA University with the capabilities of Security Analytics and Security Orchestration, Automation and Response (SOAR). The SOC is a 12- seater with four visual displays and has LogRhythm as the SIEM is Python and Spark-based indigenously developed, security analytics platform. 6. Post Graduate Diploma in Cybersecurity - Amity Online 

Amity University is India's leading research and innovation-driven university. It is recognized by UGC - a statutory body of higher education in India and accredited by National Assessment and Accreditation Council (NAAC ) with "A+" Grade. Careers of Tomorrow is an initiative by globally accredited Amity Education Group to offer high-end niche programmes to upskill students and working professionals for future and emerging industry requirements in the Technology space. Flagship Cybersecurity Program: Post Graduate Diploma in Cybersecurity  Duration Of The Program: 11 months Cost of the program: ₹1,55,000 (with flexible EMI options) Cities of Operation: Online - They have students from Bengaluru, Noida, Hyderabad, Chennai, Pune Course Content And USP Of The Program: Enterprises across the globe are increasingly realizing the vitality of cybersecurity. Amity’s Post Graduate Diploma in Cybersecurity will equip you with the skills needed to become an expert in this rapidly growing domain. You will learn a comprehensive approach of securing your IT Infrastructure, building intelligence for threat detection, executing cybersecurity operations, understanding ICS Security, architecting cloud-based security and achieving compliance. Not only will you learn the interdependence of Blockchain, Machine Learning and IoT with Cybersecurity but also you get real-world insights from our leading industry experts. The best-in-class Diploma fosters practical experience by learning in group projects and assignments to help you become a Cybersecurity expert. 7. Cybersecurity Certification Course - Edureka

Edureka is a global e-learning platform for live, instructor-led training in trending technologies such as AI, data science, big data, cloud computing, blockchain, and cybersecurity. They offer short term courses supported by online resources, along with 24x7 lifetime support. Edureka has an unwavering commitment to helping working professionals keep up with changing technologies. With an existing learner community of 750,000 in 100+ countries, Edureka’s vision is to make learning easy, enjoyable, affordable and accessible to millions of learners across the globe. Flagship Cybersecurity Program: Cybersecurity Certification Course Duration Of The Program: 4 weeks (weekend batch) Cost of the program: ₹14,995 Cities of Operation: Online Course content and USP of the program: Edureka’s Cybersecurity Certification Course will help learners master the basic concepts of cybersecurity along with the methodologies that must be practised to ensure information security of an organization. Starting from the Ground level security essentials, this course will lead one through cryptography, computer networks and security, application security, data and endpoint security, idAM (Identity and Access Management), cloud security, cyber-attacks and various security practices for businesses. This course is designed to cover a holistic and a wide variety of foundation topics in cybersecurity which will prepare freshers as well as IT professionals for the next level of choice such as ethical hacking/ audit and compliance / GRC/ Security Architecture and so on. This course is designed as a first step towards learning Cybersecurity. 8. Post-Graduation Program in Cybersecurity - IIDT

International Institute of Digital Technologies (IIDT) is an Institute set up under APEITA (Andhra Pradesh Electronics and IT Agency), an autonomous society of the Government of Andhra Pradesh to promote Information Technology and Electronics industry registered under the Andhra Pradesh Societies Registration Act, 2001. The purpose of this unique initiative is to ensure that the student community across India/Globe is empowered with the niche emerging technologies as well as to make the state of Andhra Pradesh a leader in India in establishing this prestigious Institution. Flagship Cybersecurity Program: Post-Graduation Program in Cybersecurity (PGP) Duration Of The Program: 11 Months Cost Of The Program: ₹5,25,000 Cities of Operation: Tirupati and Andhra Pradesh Course content And USP Of The Program: IIDT has three differentiators:  The pedagogy, which is based on academic and industry collaborations for the course content creation as well as deliveryThe advanced Cyber Range Lab with the creation of Centers of Excellence (CoE), to give deep-digital exposure, through real-life use-cases and projectsGlobal mentor-network, to strengthen the industry exposure to the students The Govt. of Andhra Pradesh has chosen Gujarat Forensic Sciences University (GFSU) as the Academic Partner to deliver the one-year full-time postgraduate program in cybersecurity at IIDT. GFSU, with expertise in conducting widely acclaimed Cybersecurity program for the past six years, has designed the curriculum, is delivering the program and collaborating with IIDT for placements. IIDT is setting up Cyber Range Lab operational along with 3 Centers of Excellence (COE)’s in collaboration with CISCO, Kii Corporation, T4U. 9. Cyber Pro Track - PurpleSynapz

PurpleSynapz is a hyper-realistic research and training lab designed to pave the way for the next-gen cybersecurity professionals. It aims at building the pipeline of cybersecurity talent to dent the shortage of required professionals in India. PurpleSynapz features Modern Curriculum crafted by India’s leading infosec practitioners and consultants, Cyber Range, and Innovation Sandbox that focuses on promoting the next-gen cybersecurity entrepreneurs.  Flagship Cybersecurity Program: Cyber Pro Track Duration Of The Program: 6 Months Classroom-Based Program (Including 2 Months of Hands-on Internship) Cost Of The Program: ₹3,00,000 + GST Cities Of Operation: Bengaluru Course Content And USP Of The Program: Cyber Pro Track is a six-month full-time certification course designed by one of the Industry's leading Infosec practitioners and consultants. The program features a modern curriculum spread in 14+ different modules and a hyper-realistic simulation lab (Cyber Range) that allows participants to fight real-life cyber attacks in a controlled environment. The range offers a catalogue of training scenarios, including incident response, pen-testing, OT security, and individual skill-building.  Program Overview includes 14+ modules covering networking, checkpoint, deep packet inspection, firewalls, SIEM, incident response, cyber range and many other latest technologies, along with two months internship, and free access to Cyber Range. 10. Certified Information Security Consultant - Institute of Information Security

The Institute of Information Security is one of the most trusted sources of hands-on training in information security, providing excellent unmatched practical training to individuals and corporates around the globe for over a decade. With the backing of our brilliant technical team providing consulting services for the past 18 years under the brand name of Network Intelligence, they are here to train, mentor and support your career in cybersecurity. Keeping in mind the requirements of the industry, our training programs are designed to prepare the candidates/professionals attending our training to meet the challenges they will be facing in real-life situations. Flagship Cybersecurity Program: Certified Information Security Consultant Duration Of The Program: 6 months Cost of the program: ₹1,30,000 + tax for weekday batches, and ₹1,45,000 for weekend batches Cities Of Operation: Dubai, Mumbai, Pune, Bengaluru, Chandigarh, Delhi, HyderabadCourse Content And USP Of The Program: Course content includes fundamentals, network security, coding, server security, web application security, mobile security, digital forensics, and compliance. The CISC training is designed to make you an expert in the domain of cybersecurity. While most certification programs are geared towards purely technical know-how, the CISC also arms you with the necessary consulting skills to help you make your mark in this exciting field. CISC covers a wide variety of topics, starting right from the basics, and then leading up to compliance standards, and even forensics and cybercrime investigations. CISC includes over 45+ sessions, including the fundamentals as well as advanced concepts. These 45+ sessions will be divided into four quarters, all of which will be covered in 6 months. Each session will be further broken down into 15-20 modules. Read the full article

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This PG Diploma By upGrad & IIIT-Bangalore Lets You Upskill In Data Science With 5 Specialisations To Choose From

The ‘teen’ decade saw data science transitioning from an industry buzzword to being adopted across various enterprises and applications on a giant scale. More and more Indian businesses are now using data science to understand how they can make their processes more efficient. One of the key reasons behind this is also the generation of big data. As companies are becoming competitive and are wary of being left behind, this has driven the demand for professionals skilled in data science and analytics. The trend is clear — professionals who are skilled in data science are being rewarded, along with a rising emphasis on upskilling keeping data, artificial intelligence and machine learning in the centre. As analytics and machine learning reach deeper into organisational operations, it can be clearly seen that there is significant disruption at the workplace with data scientists and data analysts preferring to experiment with newer tools. Skills are evolving and are constantly being aligned according to the industry standards and requirements. In 2019, the analytics industry grew to $3.03 billion in size and is expected to double by 2025. This growth can also be seen in the rising salaries, as with sectors like Telecom offering the highest median salary for data scientists at ₹18 lakh per annum. This is followed by the Media and Entertainment industry, which offerest a median salary of ₹10 lakh per annum to data scientists and analysts.

To bridge this gap in demand and supply, noted online education platform upGrad has collaborated with acclaimed global academic institute IIIT-B to offer a one-of-its-kind, academically rigorous and industrially relevant PG Diploma in Data Science. What Makes A Data Science Programme Truly Great? The PG Diploma in Data Science by upGrad will feature the IIIT-B's faculty discussing the conceptual depths of topics such as Data Science, Machine Learning, AI and Big Data Analytics, among others. This will be complemented by industry-relevant case studies from major industry verticals by industry leaders from upGrad's industry network. Further, their strong placement network, industry mentorship and the credibility of a PG Diploma will provide the learners with the perfect push to accelerate their careers in Data Science.  This PG Diploma by upGrad will help Data Science aspirants upskill and learn job-relevant skills with a customised Five Track course. Being the only ed-tech startup in the market that is offering this level of personalization to keen aspirants looking to upskill, upGrad’s PG Diploma programme will help students understand data science by not only going into the depth of the subject, but also by addressing the key challenges faced by the aspirants. About The Programme After analysing and understanding the key factors, depth, as well as the challenges faced by learners, upGrad and IIIT-B, divided the programme into five tracks. Each track has specific projects, assignments, topics which would be aligned to the learners background to help them strengthen their command over the subject and help them leverage business expertise and team/project/client management skills. After impacting 10,000 working professionals and delivering 2 million hours of learning experiences, upGrad concluded that there needs to be a separate track or a specialisation for every data science aspirant so he/she can get the career outcome he/she is aiming for. The critically-acclaimed data science programme, which has also been ranked among the Top 5 programmes by Analytics India Magazine, has now been divided into five tracks based on the following career outcomes: 1. Business Intelligence Entry-level role in the data industryIdeal for freshers and professionals up to 3-4 years of work exSpecialization in SQL and NoSQL Databases, and Storytelling with Advanced Visualisation 2. Business Analytics A role which required a high-level understanding of data with solid domain expertiseIdeal for professionals with 3+ years of experience with a good understanding of the domain they’ve worked inSpecialization in Advanced Machine Learning and Business Requirements - including but not limited to - advanced SQL, business problem solving through various frameworks, revenue and operational cost modelling, etc. 3. Natural Language Processing Specialisation A technical role requiring a good understanding of predictive modelling and statistics. This is a data scientist role with specialisation in NLPIdeal for people having a technical background/prior experience in a data roleSpecialization in Advanced Machine Learning and Natural Language Processing 4. Deep Learning Specialisation A technical role requiring a good understanding of predictive modelling and statistics. This is a data scientist role with specialisation in Deep Learning and Neural NetworksIdeal for people having a technical background/prior experience in a data roleSpecialization in Advanced Machine Learning and Deep Learning 5. Data Engineering A highly technical role requiring a good understanding of programming and dataIdeal for people with a software engineering backgroundSpecialization in Data Modelling, SQL and NoSQL Databases, Big Data, and Building Data Pipelines This division was thoughtfully created to make the program more focused on specific career outcomes. This efficient approach chalked out by upGrad and IIIT-B also reduces the learning time per week — since learners will focus on specific skills.  Outlook Over the last year, the data science and analytics industry accounted for 21% of the whole IT/ITeS industry in India in 2019. The analytics outsourcing industry is led by Indian IT bellwethers like TCS, Wipro, Genpact, Tech Mahindra, HCL Infosystems among others that form 35% of the analytics outsourcing market. Enterprises across the board are building up their analytics capabilities and analytics has become the biggest revenue driver for Indian IT bellwethers, captives and domestic firms within their digital portfolio. It is, therefore, the need of the time to have an efficient, timely and optimal education in upcoming and emerging subjects like data science and analytics. A degree like the PG Diploma in Data Science by upGrad and IIIT-B will make sure that the learning is well-equipped to handle this shift towards intelligent automation, AI and machine learning which is changing the face of data and analytics services. Read the full article

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This PG Diploma By upGrad & IIIT-Bangalore Lets You Upskill In Data Science With 5 Specialisations To Choose From

The ‘teen’ decade saw data science transitioning from an industry buzzword to being adopted across various enterprises and applications on a giant scale. More and more Indian businesses are now using data science to understand how they can make their processes more efficient. One of the key reasons behind this is also the generation of big data. As companies are becoming competitive and are wary of being left behind, this has driven the demand for professionals skilled in data science and analytics. The trend is clear — professionals who are skilled in data science are being rewarded, along with a rising emphasis on upskilling keeping data, artificial intelligence and machine learning in the centre. As analytics and machine learning reach deeper into organisational operations, it can be clearly seen that there is significant disruption at the workplace with data scientists and data analysts preferring to experiment with newer tools. Skills are evolving and are constantly being aligned according to the industry standards and requirements. In 2019, the analytics industry grew to $3.03 billion in size and is expected to double by 2025. This growth can also be seen in the rising salaries, as with sectors like Telecom offering the highest median salary for data scientists at ₹18 lakh per annum. This is followed by the Media and Entertainment industry, which offerest a median salary of ₹10 lakh per annum to data scientists and analysts.

To bridge this gap in demand and supply, noted online education platform upGrad has collaborated with acclaimed global academic institute IIIT-B to offer a one-of-its-kind, academically rigorous and industrially relevant PG Diploma in Data Science. What Makes A Data Science Programme Truly Great? The PG Diploma in Data Science by upGrad will feature the IIIT-B's faculty discussing the conceptual depths of topics such as Data Science, Machine Learning, AI and Big Data Analytics, among others. This will be complemented by industry-relevant case studies from major industry verticals by industry leaders from upGrad's industry network. Further, their strong placement network, industry mentorship and the credibility of a PG Diploma will provide the learners with the perfect push to accelerate their careers in Data Science.  This PG Diploma by upGrad will help Data Science aspirants upskill and learn job-relevant skills with a customised Five Track course. Being the only ed-tech startup in the market that is offering this level of personalization to keen aspirants looking to upskill, upGrad’s PG Diploma programme will help students understand data science by not only going into the depth of the subject, but also by addressing the key challenges faced by the aspirants. About The Programme After analysing and understanding the key factors, depth, as well as the challenges faced by learners, upGrad and IIIT-B, divided the programme into five tracks. Each track has specific projects, assignments, topics which would be aligned to the learners background to help them strengthen their command over the subject and help them leverage business expertise and team/project/client management skills. After impacting 10,000 working professionals and delivering 2 million hours of learning experiences, upGrad concluded that there needs to be a separate track or a specialisation for every data science aspirant so he/she can get the career outcome he/she is aiming for. The critically-acclaimed data science programme, which has also been ranked among the Top 5 programmes by Analytics India Magazine, has now been divided into five tracks based on the following career outcomes: 1. Business Intelligence Entry-level role in the data industryIdeal for freshers and professionals up to 3-4 years of work exSpecialization in SQL and NoSQL Databases, and Storytelling with Advanced Visualisation 2. Business Analytics A role which required a high-level understanding of data with solid domain expertiseIdeal for professionals with 3+ years of experience with a good understanding of the domain they’ve worked inSpecialization in Advanced Machine Learning and Business Requirements - including but not limited to - advanced SQL, business problem solving through various frameworks, revenue and operational cost modelling, etc. 3. Natural Language Processing Specialisation A technical role requiring a good understanding of predictive modelling and statistics. This is a data scientist role with specialisation in NLPIdeal for people having a technical background/prior experience in a data roleSpecialization in Advanced Machine Learning and Natural Language Processing 4. Deep Learning Specialisation A technical role requiring a good understanding of predictive modelling and statistics. This is a data scientist role with specialisation in Deep Learning and Neural NetworksIdeal for people having a technical background/prior experience in a data roleSpecialization in Advanced Machine Learning and Deep Learning 5. Data Engineering A highly technical role requiring a good understanding of programming and dataIdeal for people with a software engineering backgroundSpecialization in Data Modelling, SQL and NoSQL Databases, Big Data, and Building Data Pipelines This division was thoughtfully created to make the program more focused on specific career outcomes. This efficient approach chalked out by upGrad and IIIT-B also reduces the learning time per week — since learners will focus on specific skills.  Outlook Over the last year, the data science and analytics industry accounted for 21% of the whole IT/ITeS industry in India in 2019. The analytics outsourcing industry is led by Indian IT bellwethers like TCS, Wipro, Genpact, Tech Mahindra, HCL Infosystems among others that form 35% of the analytics outsourcing market. Enterprises across the board are building up their analytics capabilities and analytics has become the biggest revenue driver for Indian IT bellwethers, captives and domestic firms within their digital portfolio. It is, therefore, the need of the time to have an efficient, timely and optimal education in upcoming and emerging subjects like data science and analytics. A degree like the PG Diploma in Data Science by upGrad and IIIT-B will make sure that the learning is well-equipped to handle this shift towards intelligent automation, AI and machine learning which is changing the face of data and analytics services. Read the full article

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MLDS 2020: Top 10 Talks You Should Definitely Attend This Year

The second edition of the Machine Learning Developers Summit (MLDS 2020) has already started to create a significant excitement and buzz in the industry. The event, which is to be held on 22-23 Jan in Bengaluru and on 30-31 Jan in Hyderabad, is set to be one of the biggest gatherings of developers in India. With over 1,500 attendees expected to attend the event, MLDS will see innovators from leading tech companies gathering together to discuss the latest software architecture of ML systems, producing and deploying the newest ML frameworks, addressing the challenges faced and more.  In this article, we are listing down ten such discussions and talks that you can look forward to attending at MLDS 2020. These talks are a combination of keynotes, panel discussions, tech talks and knowledge talks:  1. Ecosystem Intelligence, The Next Frontier In AI When: 31 Jan, 11:30 am, Hyderabad By: Shailesh Kumar, Chief Data Scientist, CoE AI/ML at Jio Faculty for Advanced Management Programme in Business Analytics at ISB Like any other technology, AI has been growing in a bottom-up manner. Shailesh Kumar says that we have mastered the art of building accurate AI models, deploying them at scale, and continuously improving them as more data comes. We have done that for a variety of AI API's now. He says that humans are now ready to build the next-generation products that can utilize these AI API's like an ecosystem and deliver products that will be vastly different from what we think of products today. In this talk, Shailesh Kumar will explore what such products look like and how our AI and product thinking have to evolve to build such products. 2. Humans Not Machines Will Build The Future When: 22 Jan, 12.10 pm, Bangalore By: Vivek Kumar, Managing Director at Springboard India Vivek Kumar says that since we live in the age of machine learning algorithms setting to help humankind with Siri and Alexa, made a quantum leap. In such a world, do you need humanness? This talk will touch upon humanness in the age of AI-ML and how it impacts careers in these future technologies. Springboard is a company built on humanness, and this talk will throw light on how to become a better AI engineer while also helping the community of aspirants. 3. Deep Learning With TensorFlow When: 23 Jan, 12.10 pm, Bangalore By: Mohan Kumar Silaparasetty, Co-Founder, CEO at Trendwise Analytics 4. Building An AI-First Organization When: 22 Jan, 2.40 pm, Bangalore | 30 Jan, 10 am, Hyderabad By: Sundara Ramalingam N Head of Deep Learning practice at NVIDIA India This talk will focus on how to create a successful recipe for building AI into the existing traditional workflows of an organization. Machine learning, deep learning and data sciences have evolved extremely fast in the recent past, and practitioners find it challenging to keep in pace with the technology. The talk will cover the latest advancements in AI technology from both infrastructure and software perspective and recommends the best practices learnt from multiple domains for setting up a successful AI practice. 5. Deep Learning Using Convolution Neural Network For Classification Of Images When: 30 Jan, 11:30 am, Hyderabad By: Mohammad Shaheer Zaman Senior software engineer at AMD Machine learning has found its application in various practical domains. In this presentation, Mohammed will look at how deep learning can be used to classify images. Specifically, he will look at convolution neural networks which are a subset of deep learning models to solve a classic problem of computer vision which is to differentiate between two sets of images. Finally, he will compare the performance of machines as opposed to those of humans in recognizing images. 6. Anthropomorphism in Conversational User Interfaces When: 23 Jan, 4:10 pm, Bangalore By: Mathangi Sri Head of Data Science at PhonePe Machines may have "artificial" intelligence, but they want you to believe that they are humans. Can they behave like humans? Does it make sense, or is it better to go all out and declare the truth to the users?. If we want them to take human characteristics, what can be done?. What is the state-of-the-art in anthropomorphic systems, and how can machine learning and NLP help? In this talk, Mathangi attempts to break into the surface of this problem. 7. Advances in Deep Recommender Systems & Their Impact on Top Lines When: 22 Jan, 4:50 pm, Bangalore By: Bhavik Gandhi Director, Data Sciences and Analytics at Shaadi.com 8. Are We Ready For AI DevOps? When: 23 Jan, 1:50 pm, Bangalore By: Sunil Kumar Vuppala, Director - Data Science at Ericsson Global AI Accelerator This talk discusses the basic W & H questions (what, why, where, when and how) of AI DevOps and the challenges in adoption of deploying the ML/DL models. This covers a couple of reference frameworks in this journey such as MLFlow, SageMaker and Azure ML service. Sunil also includes a couple of use cases from the Telecom industry to illustrate the need for faster diagnosis and edge deployment. He highlights various trade-offs one needs to handle in their ML life cycle, including the PLASTER framework. The key takeaways for the audience will include essential factors to be considered while designing and deploying the DL based solutions, take steps towards AI DevOps and corresponding research areas to work on. 9. Boosting Memory-Based Collaborative Filtering Using Content-Metadata When: 23 Jan, 4.50 pm, Bangalore By: Anish Agarwal Director – Data & Analytics at RBS India Recommendation systems are widely used in conjunction with many popular personalized services, which enables people to find not only content items they are currently interested in, but also those in which they might become involved in future. Many recommendation systems employ the memory-based collaborative filtering (CF) method, which has been generally accepted as one of the consensus approaches. Despite the usefulness of the CF method for a strong recommendation, several limitations remain, such as sparsity and cold-start problems that degrade the performance of CF systems in practice. In this talk, Anish will talk about how to overcome these limitations, a suitable content-metadata-based approach that effectively uses content-metadata. 10. AI in Manufacturing Intelligence When: 31 Jan, 09:15 am By: Venugopal Jarugumalli Principal Solutions Architect at ZF Group Artificial intelligence technology is now making its way into manufacturing, and the machine-learning technology and pattern-recognition software at its core could hold the key to transforming factories of the near future. AI will perform manufacturing, quality control, shorten design time, and reduce materials waste, improve production reuse, perform predictive maintenance, and more. Read the full article

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The Hitchhiker’s Guide To Artificial Intelligence 2019-2020: By AIM & Great Learning

In the last decade, we have seen AI transitioning from an industry buzzword to finally being adopted across various enterprise applications. Indian businesses are analysing how they can make processes more efficient which has led to increasing adoption of artificial intelligence in the enterprise across different verticals. Products and services are being rebuilt with the integration of artificial intelligence with the objective of creating a better experience for end consumers. As enterprises are wary of getting left behind, this has driven the demand for professionals skilled in AI-based technologies. The trend is clear— professionals who are skilled in AI are being rewarded, along with a rising emphasis on upskilling keeping artificial intelligence in the centre. In collaboration with Great Learning, we have started tracking the AI industry in India over the last two years. The result of the partnership is our annual AI study- The Hitchhiker’s Guide to Artificial Intelligence 2019-2020: By AIM & Great Learning, where we look at the key AI trends dominating the Indian AI market. The study covers professionals, salaries, AI jobs across different Indian cities, and the companies leading in terms of AI hiring in the country. The most significant outcome of the study is the much-accelerated growth of the AI industry since last year. Growing by 80%, we see AI is no longer in a hype stage and has observably entered the period of real productivity. In fact, a WEF report states over 133 million new roles will surface due to AI over the next two years. It is therefore clear that in the coming years, there are going to be many more vacancies in the AI sector, than the number of skilled talent available. The trend is already visible in many enterprises, as most companies fail to implement planned AI projects due to a lack of skilled talent. In the second half of the report, we cover AI literacy in India through Great Learning’s comprehensive AI/ML programs that are bridging the gap and consequently boosting workforce transitions. Research Methodology The Hitchhiker’s Guide to Artificial Intelligence 2019-2020 is a result of a six-month-long survey where we sought responses from Indian professionals in Artificial Intelligence and Machine Learning industry with varying years of experience-- ranging from freshers to mid and senior-level executives. Each respondent was questioned on his/her location, work designation, income level, educational background, experience level, industry type, company size, and tools and aptitudes they use in the profession. The respondents were active across different business verticals including customer service, BFSI, medicine and healthcare, retail, e-commerce, IT products and services and manufacturing. The research methodology also incorporated an efficient arrangement to distinguish the different elements impacting work situations around artificial intelligence in India. Multiple data points were gathered after communicating with organizations across all major cities in India. Key Trends The Indian AI market size in 2019 has broken out of the trend that we had seen the years before. This year, the overall market size witnessed a dramatic jump in terms of market growth, which is a great sign for the industry. Here are the key trends of the AI market in India that we found out: Artificial Intelligence Industry in India is currently estimated to be $415 million annually in revenues, up from $230 million a year ago.AI Industry grew by a healthy annual rate of 80% last year. This is an extremely high increase, peculiar with technologies that are in early stages of adoption. This is a remarkable jump since last year when the industry growth was estimated to be 28%. In 2019, there are approximately 72,000 AI professionals in India. This is an 80% increase from the year prior when there were 40,000 professionals in AI.

Section 1: AI Professionals In India

At a time when there is an apparent shortage of AI skills, skilled professionals have been critical for the growth we have seen in the last year. Here are the findings of the study that concern the demographics and experience levels for AI professionals:  Out of the 72,000 AI professionals, around 6,000 freshers were added to AI workforce in India in 2019. The number was 3,700 in 2018. The average work experience of AI professionals in India is 7.2 years — than 6.6 years from last year.Almost 51% of AI professionals in India have a work experience of less than 5 years, which is the same as last year.29% of AI professionals have more than 10 years of work experience. This work ex is not necessarily in AI but these professionals have transitioned into AI over time. Women participation in AI workforce remains low – only 26% of AI professionals in India are women. This is still a slight increase from 2018, when the share of women in the Indian AI workforce stood at 24%.

AI Talent Divide Across Companies  Here we track the spread of AI professionals across different organizations based on employee size. While the trend remains somewhat the same as last year, we found the proportional size of AI professionals increased in large organizations. Almost 39% of AI professionals in India are employed with large-sized companies – with more than 10,000 total employee base. Here, we witness an increase from 2018 when such organizations had employed 37% of the AI workforce.Mid-sized organizations (total employee base in a range of 200-10,000) employ 29% of all AI professionals in India.Startups (less than 200 employees) account for 32% of AI professionals in India. This number has come down from 34% in 2018.

Tenure Looking at how long AI professionals have been working in this specific technology domain, we find that there is a clear shift. New professionals are increasingly recognising the AI opportunity and making a transition. On average, AI professionals in India have joined/transitioned to their current role in the last 3 years.65% of AI professionals in India have joined/transitioned to their current role in the last 2 years.These stats signify that AI is a very recent technology and a huge number of professionals are gravitating towards it.

Cities In India, there are only a handful of destinations for AI professionals and similar to last year, not much has changed in this regard. India’s metropolitan IT hubs is where professionals need to be to snatch the best work opportunities in artificial intelligence space. Here is what we witnessed for 2019:  Bengaluru leads again in terms of the size of the ecosystem as 32% of AI professionals in India are working in the city in 2019.This is closely followed by Delhi NCR at 24%.In 2019, Pune has surpassed Chennai in terms of the percentage share of AI professionals.Hyderabad’s share remains the same this year at 11%, whereas Mumbai saw a decline in its contribution to India’s total AI professionals, falling to 12% from 14% in 2018. Education Advanced jobs correlate with advanced degrees, and the fact is evidential from our findings when it comes to the AI professionals. Here are the findings: 48% of AI professionals have a Master’s/ Post Graduation degree, same as last year.2.6% of AI professionals in India hold a PhD or Doctorate degree.

Section 2: AI Companies In India

We see that there is a growth rate of almost 200% year over year in the number of AI companies in India since 2018. This shows the proliferation of AI in the enterprise space, confirming that companies are catching onto the opportunity in an exponentially fast rate.  Indian tech behemoths TCS and Infosys have paced up their hiring in the emerging tech sector manifold. Numbers show that TCS has increased their hiring in IT by 377% and Infosys by 642%.More than 3,000 companies in India claim to work on AI in some form. This includes a small number of companies into products and a larger chunk offering either offshore, recruitment and training services. Last year, we had found that 1,000 companies reported using AI. The number of AI companies in India are still very few in number, compared to the strength of analytics companies around the globe. In fact, India accounts for just 12% of global analytics companies. In 2018, we found that Indian companies accounted for 8% of the global share, which indicates a noteworthy growth.  Company Size On average, Indian AI companies have 81 employees on their payroll. This is slightly lower from 87 last year.Almost 83% of analytics companies in India have less than 50 employees, slightly less from last year at 85%. As seen from the graph, the number of AI firms with less than 10 employees have decreased from last year and an increase is seen in the number of firms with 200-500 employees.

Cities Bangalore leads other cities to house the most number of AI firms in India this year, at almost 31%.It is followed by NCR at 25% and Mumbai at 14% AI companies.Hyderabad, Chennai and Pune are far behind with their percentages of analytics companies in single digits as reflected in the graphs above.

Section 3: AI Salaries in India

In the previous section, we mentioned that that three thousand businesses in India are leveraging AI professionals to create operational value across functions in 2019. The AI market size has seen a tremendous shift upwards since last year, hence, salaries remain attractive for professionals to take notice.  The median AI salary in India is INR 14.7 Lakhs across all experience level and skillsets. This is almost the same as last year.38% of AI professionals in India command a salary of less than 6 Lakhs. Almost 4% of AI professionals in India command a salary higher than INR 50 Lakhs

Salary Trend Across Cities Mumbai is the highest paymaster in AI at almost 17 Lakh per annum as median salaries, followed by Delhi/ NCR at 15.6 Lakh.Chennai is the lowest paymaster at 10.8 Lakh.

Section 4: AI Jobs in India

In this section, we look at the number of AI positions in India currently, and the companies offering the most vacancies. The key finding is that compared to 2018, there are fewer AI positions waiting to be filled. Additionally, we observed that India’s contribution to AI-related job openings declined slightly despite it being already small compared to the AI job openings worldwide. While, it is difficult to ascertain the exact number of open AI job openings; according to our estimates, close to 2,500 positions related to AI are currently available to be filled in India.Compared to worldwide estimates, India contributes 7% of open job openings currently. Growth in the number of AI jobs globally was much higher than India.Our numbers suggest that the top 10 leading organisations with the most number of AI openings this year are – IBM India, Accenture, 24/ 7 Customer, Nvidia Corporation, Hewlett-Packard, Ernst & Young, Genpact, Amazon, eClerx Services & Capgemini.Almost 92% of AI jobs advertised in India are on a full-time basis, rest are part-time, internships or contract basis jobs. AI Jobs By Cities In terms of cities, Bengaluru accounts for around 36% of AI jobs in India. This is down from 37% last year.Delhi/ NCR comes second contributing 17% AI jobs in India. This is down from 30% last year.Approximately 11% of AI jobs are from Mumbai, almost the same as last year.

Salary Requirement for AI Jobs The salaries advertised for jobs are usually substantially lower than the actual salaries offered in the industry.On a median, the AI jobs advertised in India are offering a salary of 11.6 Lakhs per annum. This is substantially lower than the actual salary median of 14.7L for AI professionals.

Conclusion

The Hitchhiker’s Guide to Artificial Intelligence 2019-2020: By AIM & Great Learning found a steady growth in AI field in India, both in terms of market growth and the number of professionals added to the analytics workforce. Looking at the increasing number of jobs in AI, coupled with the void created due to the lack of skilled mid and upper-level management, education is one of the crucial ways this talent gap can be filled. In a modern enterprise, AI is not only needed at a product and development-level, but it is also of vital importance in decision-making. The key trends that we predict we will see in 2020 revolve around the mass acceptance and usage of artificial intelligence at an enterprise as well as consumer-level. New trends such as explainable AI, augmented analytics, hyper-automation and quantum computing, among others, are paving the path for creation and usage of advanced products and services to look forward to in 2020. Some of the other important trends we suggest that readers look forward to are: Large scale adoption of business intelligenceRising AI-based optimization of enterprise processesImproved data management across Indian organizationsIncreasing use of chatbots and NLP voice assistants from end consumersBigger AI budgetary allocations from the government

You can access the full report here:

https://www.slideshare.net/mailpraj/hitchhikers-guide-to-ai-201920-by-aim-gl Download the complete report THE HITCHHIKER’S GUIDE TO ARTIFICIAL INTELLIGENCE 2019-2020Download Read the full article