Untitled

[joydcosta]

What are the pre-requisites to start a career in Data Science?

A data scientist is a highly demandable profession these days. As per NASSCOM report, there will be a rise in the demand for data scientist jobs by 40% in the year 2020. Data analytic industry is expected to have a market share of more than USD 15 billion by 2022. Data scientists are highly qualified persons and qualifications for same range from Bachelors degree to PhD.  The key role played by a data scientist is to gather, analyze and interpret the data that requires high skill sets. A data scientist should have a good academic and technical language which helps in understanding the data and course in a better way, however, academic excellence is not the only criteria to become a data scientist. One who is interested in learning the things and understanding the logic may excel in this field.

Fusion Technology Solutions provides Online Data Science Course that help you understand deeply about all the concepts and give kick start to your career.

The pre-requisites required to start a career in data science can be categorized into two factors.

1. Non- technical or fundamentals skills.

2. Technical skills

Non-technical skills are those which you learn during your academic period. These are the basics that include math, and statistics. It is considered that statistics is the core of the data science learning and one should be aware of the fundamentals of same. It is further subdivided into-

1.    Descriptive statistics

2.    Inferential statistics

Descriptive statistics are more descriptive in nature and is normally represented in the forms of graphs. Type of Descriptive statistics are-

1.    Normal Distribution

2.    Central Tendency

3.    Kurtosis

4.    Variability

Inferential statistics focuses on the conclusion part and provides an explanation related to the data or statistics.

One should also be good at math for analyzing and understanding the vast data. You should be well versed with basic mathematics like linear algebra, calculus, and probability.

We will now focus on the technical skills one should have to understand data science. Technical skills are the one which is not taught directly into your academic curriculum, however, need to be acquired separately to widen your knowledge. Some of them are like:

Ø  Excel- Excel is considered to be a good start for the beginners, it teaches you how to short the data, work on it, creating the charts and tables, filtering the data and most important analyzing the data. It also involves representing the data in the form of pivot tables.

Ø  Python- Python has gained its popularity in these few years due to its ease if codding and understanding of language. It is considered to be one of the easiest languages one can learn without having prior knowledge of programming before. Python has the vast presence of libraries and packages which makes it easier for the user.

Ø  R- It is one of the required languages one should know if you are entering into the data science field. It is also one of the easiest languages but not as easy as Python is. The beginner's mat find it difficult to understand and learn, however, practice makes nothing impossible. R also contains large libraries database and it is one of the best statistical tools in use.

Ø  SQL- Known as a structured query language is one of the oldest database query language being in use. It is one of the most important languages one should learn to become a data scientist. SQL is used to mine data from the database, which contains a vast amount of data structured in the manner of rows and columns of a table.

Other than this one should have good communication skills to understand and interpret the data given by your clients. It is important that you must be able to convey your ideas and logic to your superior and to your clients. An understanding of business models and its functions are also mandatory, that helps in identifying the actual need of your clients and its solutions. For more information on data science I would recommend the Best Data Science Institute 

[joydcosta]

What is a data scientist's career path?

Understanding who is a data scientist?

A data scientist is a person who is able to collect the data, analyze and interprets the data, having technical skills and should be able to solve the complex problems.

Who can become a data scientist?

Any individual who belongs to technical and no technical field and has a prior experience in a particular domain or is a fresher can become a data scientist. 

Role of a data scientist in the organization?

The role of a data scientist varies from position to position. At the initial stage of data scientist career, one gets an opportunity to enter in the role of an executive level, who is trained to handle the different MIS(Management Information System), generate and create CRM(Customer Relationship Management). After years of experience, one gets a chance to become an analyst and then business analyst, who performs complex tasks like data mining, programming, use of advanced statistics, business process handling, and data engineering. One who gets a prior knowledge of these domains, you get a chance to shift for the next job role as a data architect, where one has to work on data warehousing, data cleaning, and data modelling. Your job role may vary from organization to organization and there are no set rules under work environment. You are therefore promoted to chief data officer or scientist whose responsibilities are wider in range and involves working on algorithms, big data processing, and introducing to new technologies.

 Data scientist career path.

This section is broadly divided and is explained in the following manner. There are various levels which one has to cross in order to get trained and gain expertise in data scientist career. Fusion Technology Solution is one of the Best Data Science Institutes in Pune which provides Best Data Science Course.

Level 1- Associate or Junior data scientist.

As explained before a person having no technical knowledge can be a data scientist too, however, there is a specific skill set required which one needs to be aware of. By the name of the job role, you must be aware that a data scientist needs to deal with a large amount of data and one need to be technically fit to understand and analyze the data. You shall be taught with the basics of programming languages during the initial stages of your learning. A theoretical and practice training shall be there during the course that will make you aware of the programming languages like Python, Java, R, and SQL(Structured Query Language). You are now set to enter in this job role and shall be able to handle the given data in the MIS.

 Level 2- Data scientist mid-level-I

One after having years of experience you may switch to the next level of your career, where you will get an opportunity to become a data analyst and Artificial Intelligence/ Machine Learning engineer. This is a level where one needs to have a good understanding of data. Any additional certification with one will help to get a good position within the organization. One who is having this job role need to get into the core of the data and has to find the flaws in the previous models, write the codes and building a structured pipeline.

Other than analyst post, one gets an opportunity to be an AI & ML engineer, where one needs to have a   very good command on different languages like C++, Java, Python, SQL, and software engineering. Data processing, data mining, designing, evaluating and deployment will be the core level of activities.

 Level 3- Data scientist mid-level-II

One who reaches this position should have a good understanding of the business structure of any organization. How the organization structure is flowing and what are the flaws within the organizational management studies. One should be able to shape and structure the data, prepare strategies and conveying them to the senior management for any specific changes. One has the opportunities to be a data scientist architecture, who should have both technical and non-technical abilities. One should be good in programming languages and must be holding certifications other than data scientist to recognition within the organization.

Level 4- Data scientist advanced level.

This is the highest level where your skills will be tested. One should have knowledge of understanding the complete structure of data flow and shall have the leadership qualities to guide your subordinates and handle the team. You shall be in a position where your experience will count.

Concluding the above information, we can figure out that, a career in becoming a data scientist is very lucrative and joyful. If you have a high aim of becoming good data scientists and you have a keen interest in visualizing the data, churning the data, you will be happy working as a data scientist.