oh yeah, over the past few days i've had another interview and a coding assessment
first interview in Rust went okay but. well. it was an easy problem and i immediately came up with a trivial O(n^2) solution and started to think out loud about how to optimize it further. and then the interviewer said "well we don't actually care about the optimal solution, anything polynomial will do fine." so i stopped thinking and implemented my O(n^2) solution.
and then as soon as i got out of the interview, i thought up a clever way to get to O(n) that *also* would've simplified the code a lot. which pissed me off. i think going forward i am going to say "hey, so i've noticed that if i try and verbalize my thoughts continuously at the start of an interview, i don't get a good grasp on the problem, so if it's all right with you i'm going to set a timer for 3 minutes and just think without talking." and then do it. because this is twice now that i've felt like this.
coding assessment was pretty easy - finished with 17 minutes to spare out of 90 and all tests passed. i chose Python instead of Rust because i knew it was going to be OOP but in retrospect i think that might've been a mistake? or at least, it seems like it would be worthwhile to get comfortable enough with Rust's structs and traits that i don't feel pressured into using Python - i had a number of Pythonic issues that would've been caught in a strongly-typed language (they didn't have typechecking in the assessment, tragically).
anyway - i'm nitpicking, objectively both the interview and the assessment went great. but they were also both objectively pretty easy and i guess if you had told me in advance that i was answering questions this easy, i would've expected to do things with a bit more ease. and i expect the third company to be meaningfully more challenging than the first two, so. idk.
Artificial Intelligence (AI) has revolutionized the way we work, learn, and create. With an ever-growing number of tools, it’s now easier than ever to integrate AI into your personal and professional life without spending a dime. Below, we’ll explore some of the best free AI tools across various categories, helping you boost productivity, enhance creativity, and automate mundane tasks.
Wanna know about free ai tools
1. Content Creation Tools
ChatGPT (OpenAI)
One of the most popular AI chatbots, ChatGPT, offers a free plan that allows users to generate ideas, write content, answer questions, and more. Its user-friendly interface makes it accessible for beginners and professionals alike.
Best For:
Writing articles, emails, and brainstorming ideas.
Limitations:
Free tier usage is capped; may require upgrading for heavy use.
Copy.ai
Copy.ai focuses on helping users craft engaging marketing copy, blog posts, and social media captions.
2. Image Generation Tools
DALL·EOpenAI’s DALL·E can generate stunning, AI-created artwork from text prompts. The free tier allows users to explore creative possibilities, from surreal art to photo-realistic images.
Craiyon (formerly DALL·E Mini)This free AI image generator is great for creating quick, fun illustrations. It’s entirely free but may not match the quality of professional tools.
3. Video Editing and Creation
Runway MLRunway ML offers free tools for video editing, including AI-based background removal, video enhancement, and even text-to-video capabilities.
Pictory.aiTurn scripts or blog posts into short, engaging videos with this free AI-powered tool. Pictory automates video creation, saving time for marketers and educators.
4. Productivity Tools
Notion AINotion's AI integration enhances the already powerful productivity app. It can help generate meeting notes, summarize documents, or draft content directly within your workspace.
Otter.aiOtter.ai is a fantastic tool for transcribing meetings, interviews, or lectures. It offers a free plan that covers up to 300 minutes of transcription monthly.
5. Coding and Data Analysis
GitHub Copilot (Free for Students)GitHub Copilot, powered by OpenAI, assists developers by suggesting code and speeding up development workflows. It’s free for students with GitHub’s education pack.
Google ColabGoogle’s free cloud-based platform for coding supports Python and is perfect for data science projects and machine learning experimentation.
6. Design and Presentation
Canva AICanva’s free tier includes AI-powered tools like Magic Resize and text-to-image generation, making it a top choice for creating professional presentations and graphics.
Beautiful.aiThis AI presentation tool helps users create visually appealing slides effortlessly, ideal for professionals preparing pitch decks or educational slides.
7. AI for Learning
Duolingo AIDuolingo now integrates AI to provide personalized feedback and adaptive lessons for language learners.
Khanmigo (from Khan Academy)This AI-powered tutor helps students with math problems and concepts in an interactive way. While still in limited rollout, it’s free for Khan Academy users.
Why Use Free AI Tools?
Free AI tools are perfect for testing the waters without financial commitments. They’re particularly valuable for:
Conclusion
AI tools are democratizing access to technology, allowing anyone to leverage advanced capabilities at no cost. Whether you’re a writer, designer, developer, or educator, there’s a free AI tool out there for you. Start experimenting today and unlock new possibilities!
Hi Raina! I'd like to appeal to your hard-won wisdom on The Adult World-- do you think it's possible to teach yourself/find online resources to help learn things like data analysis? I want to look at numbers and graphs and spreadsheets for money but don't know what resources are good enough to trick capitalism and bosses into hiring me for it!
Oh, yeah, 100%
Source: I pretty much did that.
So first the disclaimers: I did have a bachelor's degree in applied mathematics, and I did shell out for an MBA as my happy-divorce-day present to myself. I know that I really don't use either of those things in my day-to-day work, but hiring managers probably are considering them when they look at my resume. I'm also white, a native English speaker, and talk like an educated middle-class suburbian, which I'm sure also play into mangers' willingness to give me the benefit of the doubt. So my exact path may not work for you.
That said, data, in particular, has several advantages right now:
1) Demand is large, and supply is small. If my department doubled in size, we could still not quite answer all of the questions the business leaders are asking of us. I don't think there's been a moment that I've worked for this company that we didn't have a least one job slot we were hiring for. In addition to making this a lucrative industry, it also makes it fairly easy to break into, because hiring managers are willing to accept far less perfect candidates if only they can get someone who knows something working on this project.
2) The field is changing very fast. No one knows what languages or software we'll be using a year from now, so it doesn't really matter that much if you don't know the one we happen to be using right now. Supervisors are much more concerned with "When it turns out we have to switch our entire reporting scheme to Scala, will you be able to learn that?" And in that context, it is incredibly encouraging to hear a candidate say that they once had to do a thing in Python but they didn't know Python so they Googled and perused Stack Overflow until they could do the thing. You are very likely to have a question at the interview that's something like "Describe a time you had to learn something quickly" or "What's your approach when you don't know how to do something?", and as an autodidact, you will have lots of examples for those moments.
3) There are lots of places that don't have anything at all. A person who knows how to put conditional formatting on a column in Excel would be an improvement on what some smaller companies are currently doing. If you can make a graph and code a vlookup() function, then you're an Expert!
4) the field is so new, and is changing so fast, we're still working out the distinctions between the assorted sub-fields. Which means you can start as someone who does data visualization, pivot to data science, change your mind and end up in data engineering, and then decide to do database administration instead.
So yeah. My recommendation is to search job boards for things that look like they might be what you want to do, and write down what the minimum qualifications are for each one. If you already meet 70% of the requirements, start applying! If not, make a li'l histogram of requirements they want and you don't have, and start finding ways to get them.
I, for instance, downloaded an SQL syllabus from some university class that had it publicly posted, and learned SQL by just doing the assignments on my own time when things were slow at the retail job I had. I got an office job on the strength of that, buuuuut my first assignment wasn't really doable in SQL, so I did the work in Python (a language that, up until that point, I had made 0 programs in, but I had watched while someone else made a program in it), and then bodged it into Excel for visualization. That made me look enough like a developer that the data science team was willing to talk to me, and so I got to sit in on the Alteryx intro seminar when they did, and then (since Alteryx was brand new and didn't really have any documentation or communities at that point) taught myself how to use it by trial-and-error. That got me enough experience that I subsequently got offered a job paying twice as much, working with BASH, hql, scala, and Jenkins (a list of coding options that -- you'll notice -- I had not yet had any experience in).
Basically, as a rule, hiring managers have no idea what all is going on behind the scenes, nor do they care, as long as they get the intended outcome. So my approach for interviews is to approach it as communication/translation problem for the first half: what exactly are they hoping the person in this position will be doing? "So, for example, {possible project based on my understanding of how they described the job}, would that be the type of thing?" Repeat until you're pretty sure you know what they're looking for. If you can do that thing, then you're justified in saying "I can do that", and you probably have evidence to back it up. So the second half of the interview is using their questions as an opportunity to lay out your evidence. Bonus: asking questions in the interview makes you look both smarter and more engaged!
If you get a technical interview/whiteboarding interview, don't panic! They're looking more at how you approach the problem than they're looking at your actual ability to write solid code / know the exact names for everything (my last interview I had to ask "What's that?" after, like, 3/4 of the questions. Then the interviewer would start describing it, and I'd be like "OH yeah, so then ....". I got the job.) So if you don't know what to do, start writing out outlines, mind-maps, lists ... whatever would help you figure out how to get started. Write down the facts of the situation, and implications of those facts; write down questions you have, and how to get them answered. This is a situation where partial credit is very VERY much a possibility, so get as many possible partial-credit sources on the whiteboard as possible.
So yeah. Coursera, Khan Academy, etc, all great. You can also just find some school that doesn't password-protect their class materials, and if you can mess around enough to solve the problems on the homework assignments, then you know (at least) as much as anyone who's officially taken that class. Alteryx and Tableau offer free online training with a web-portal sample of their software. You could also check for volunteer opportunities: I'm organizing permit applications for Sierra Club, and I bet there's a non-profit near you that would be equally delighted (read: fucking overjoyed) to let you take over all graph/numbers/spreadsheets for their projects. Then you get them to write you a letter of recommendation, and put the reporting work on your resume, and you've got "real world experience" while you're saving the world.
I wish you the best, and feel free to ask more questions as you go farther along your journey! I definitely recommend the data-work life; it's been my favorite career so far.
Google Execs Declare "Code Red" Over Revolutionary New Chat Bot
From Zero Hedge:
Three weeks ago and experimental chat bot called ChatGPT was unleashed on the world. When asked questions, it gives relevant, specific, simple answers - rather than spitting back a list of internet links. It can also generate ideas on its own - including business plans, Christmas gift suggestions, vacation ideas, and advice on how to tune neural network models using python scripts...
What's more, AI chat bots may not be telling the entire truth - and can produce answers that blend fiction and fact due to the fact that they learn their skills by analyzing vast troves of data posted to the internet. If accuracy is lowered, it could turn people off to using Google to find answers.
Or, more likely, an AI chat bot may give you the correct, perfect answer on the first try - which would give people fewer reasons to click around, including on advertising.
"Google has a business model issue," said former Google and Yahoo employee Amr Awadallah, who now runes start-up company Vectara, which is building similar technology. "If Google gives you the perfect answer to each query, you won’t click on any ads."
According to industry experts, Google will eventually need to decide whether it will overhaul its search engine to incorporate (or evolve into) a chat bot as the face of its flagship service.
"A cool demo of a conversational system that people can interact with over a few rounds, and it feels mind-blowing? That is a good step, but it is not the thing that will really transform society," suggested Zoubin Ghahramani, who oversees the A.I. lab Google Brain, in a November interview with The Times. "It is not something that people can use reliably on a daily basis."
Note: If you had read the original version on my website, I totally did not rewrite this entire part just to avoid a fight scene.
The mission was simple: save the two idiot exchange students that don’t have any common sense. It was a frustrating task to even track them down. Base on the footage from security cameras and likely villains who are crazy enough to start drama, it is very likely that the dumb and dumber are safe but being hold over a pot of acid, fire, or water will killer animals. Who knows?
“You know, they just have given us an excuse to bring the Gotham miraculous crew back into action,” Andrena says as her bee-like wings flutter to life. Her eyes narrowly focus on anything strange.
To Gotham, Andrena is equivalent to Paris’ Melitta Bee (Chloe’s new alias once she was inducted back onto the team). Every member of Paris’ MT has a Gotham counterpart. For Ladybug it was Ladybird, for Chat Noir it was Lykoi. Then for the two missing members Viperion and Ryoku, there was Python and Naga. The only difference two their styles are more realistic and less magical.
“There is no time for play, Bee.” Ladybird walks out from the shadows, the current boy wonder walking behind her. She crosses her arms and lets out a heavy sigh. “As long as we are active in the fight any damage the two may endure could be undone. You know how I hate to bring out the team.” Everyone could see the tiredness behind the red and black mask that lies in her bluebell eyes.
“Tt. They deserve whatever comes their way.” Robin scoffs. From the corner of his eyes, he could see his siblings joining them on the roof. “What did you find?” This question wasn’t pointed to anyone directly, but they all knew there was one person with the answers.
“Red Robin—” Lykoi lowkey hums ‘Yum’ much to everyone dismay “—has appointed Oracle as our eyes, and together that have determined that the two missing students are located in one of five potential areas.”
“That does not help our case, Wing.” Nightwing would never admit it but a glaring Ladybird is a dangerous Ladybird.
Silence followed as everyone thinks of something.
“Do we have to save them? They just made this worse on everybody.” It was Lykoi’s voice that surprisingly states this. Everyone turns to the cat theme hero with wide eyes. “What?”
“Normally under typical Paris standards, I would say no, but do to the fact that we are in Gotham and my job is on the line, I am legally obligated to say yes.” Ladybird pulls out her communicator and turns it on. “Everyone’s logged on.” A series of nods, groans, and yeses. “Good RR, what’s the plan?”
“Yes, but you’re not going to like it,” Red Robin could hear the impending groaning coming his way and he is not wide awake enough for this.
Which lead the Miraculous Team and the Bats to be split across Gotham searching for the two exchange students.
Ladybird and Robin’s location was empty. Nothing unusual about the location it was just an unused warehouse.
“I hate them.”
“Them being everyone or the two the idiots.”
“What do you think?”
Robin shakes his head and lets out a hefty sigh.
Lykoi and Nightwing’s location proved to be difficult to find. At first, that thought this was the place, but both heroes vigilantes were proven wrong.
“We both agree not to tell Ladybird.”
“Agree, she would kill us.”
“I heard that.” It wasn’t Ladybird’s voice that came through the comms. It was Oracle’s. “Don’t worry I won’t tell Birdie.”
Lykoi and Nightwing share a glance. It was better to be blackmailed by Oracle than be grilled by Ladybird—well that what they think anyway.
For Andrena and Red Robin, it was more of a battle of wits and smarts between the two. Actually, more on Red Robin than with Andrena (she didn’t want to be a partner with Red Hood).
“You better hope that one of the others found this fucking warehouse or I will kill you myself. These boots were expensive.” Andrena shrieks pointing to the mud that now lays pack on her boots.
“Yeah, yeah, I’ll make it up to you.”
Andrena rolls her eyes and opens her communicator, Red Robin does the same. However, the outcome was different for the two. On Red Robin’s feed, it was static, he quickly goes into work to scramble the information given. Andrena sees a message from Red Hood. It reads, “Found it, suckers!”
“Hood found the warehouse.” Andrena places her communicator back on her person and looks to Red Robin. She could see the invisible sweat and sleep on his face through the cowl. “Let’s go.”
RR lets out a frustrating sigh, but as he types a last-minute code into his device the static slowly turns into quality footage. Not high quality but enough pinpoint what is happening. The room is dark but there is an ominous green glow at the lower half of the screen.
“Shit,” RR murmurs through it was loud enough to catch Andrena’s attention as an electric blue glow begins to grow behind her.
“What?” It was breathless yet concerning. Behind her, the portal fully develops causing her to let out a low growl and pushing RR in the direction of their “ride”. “Just explain it to the others.”
The portal closes and the first person they are meet by is a somewhat disappointing Ladybird.
“Hey Buggy,” Andrena sheepishly smiles, better throw RR under the bus, “RR found something interesting. Check it out.”
Ladybird makes her way over to the bee and the third Robin, she eyes RR practically asking him the question, “what he found”. Everyone waits with bated breaths as he shows her the footage. This time unlike the awkward murky background, it shows Lila and Alya tied together on a mini platform that is slowly lowering to the ominous glow below them.
“Is it sad that I want to see them fall.” The ladybug theme hero sighs into her glove-cover hands. “Alright, we need a game plan. Hood, what did you find?”
“There is a tunnel beneath the building. There’s no exterior access.”
“Oracle is sending us a blueprint.” Red Robin adds to which Nightwing nods and checks in his own portable monitor. Robin tsks and crouches down on the ground.
The planning process to a good minute to formulate.
“Is everyone in position?” The question ran through everyone’s coms as their trained bodies wait patiently for the cue. The Questioner (most likely Ladybird or Nightwing) took their silence as an answer. “Let’s go.”
The vigilantes are immediately greeted by darkness.
“Argh, my hair!” All movement ceased to exist. The Miraculous Team automatically knew that screech. It was Lila’s. “Please, I promise Bruce Wayne will make your life worthwhile. I’m very good friends with him.” Everyone, aside from Robin, felt a shiver go down their spines. Robin had gagged at the thought of Lila, his girlfriend’s tormentor, being friends with his father.
“Are you sure we can’t kill her?” Red Hood asks, well more like stated but everyone knows what he meant. He didn’t receive an answer.
“Better yet, who’s the person that decided to capture the two. There are only two heat signatures in the building.” Tim fiercely types against his device.
Nightwing kicks down the door. The large thud grabs the two teens' attention.
“We’re saved.” Lila cries out in delight. Her face literally brightens much to everyone (aside from Alya’s) dismay.
“Yes, I can finally get that interview just like you said, gurl.” Alya squeals her body wiggling on the platform.
Robin staggers in his footsteps. Interview? Like you said? Something isn’t adding up.
“Are you girls okay?” Nightwing typically heroic voice shines through as Red Robin rushes to what he believes to be the controls for the platform.
“Uh... no, I’m Ladybird. Now hold still.” Balancing herself on the platform in front of the two, she pulls out a knife and quickly goes cuts to the first layers of rope. “We’re the villain?”
“He was getting something to surprise us.” Lila’s voice squeaks a little. Everyone pulls back to face Lila, not including Alya.
“What do you mean?” Robin fakes a cough and glares at the Italian girl.
“No, no,” Lila begins to sweat. Her mind running multiple scenarios to get out of this. “We have no idea where he went. It was pitch black for us.” Tears forms in her eyes. Alya tries to comfort her bestie but couldn’t due to their bindings.
“Red Hood, stay on high alert, Lykoi, Andrena, follow his lead.” Ladybird cuts through the final rope. Alya shuffles her feet to get away…
“Ah!” The reporter’s foot slips.
“Merde,” Ladybird deadpans and lets herself fall.
Her right arm wrap around Alya’s waist as her left grabs for the yo-yo. It was a split second; her feet did touch the unknown substance in the large pool. She was expecting a burning sensation, but nothing happens.
“What the hell, RR, get off the control and test out the substance.” Ladybird safely places Alya down on the concrete flooring. Nightwing and Robin run over to the two for different reasons. Robin pulls Ladybird into his arms and checks for any injury while Nightwing does the same for Alya. The ombre haired girl is visibly shaking.
Lila remains on the platform above the pool screeching her head off. Andrena could already sense a headache forming and flies up to the platform. “Venom!”
Lila freezes, her screaming ceases to exist.
Rather than pushing Lila off the platform (the temptation was very luring), Andrena wraps an arm around the liar and flies to the ground floor. Suppressing a shiver, she pushes the girl out of her arms and into Lykoi’s much to his dismay.
“Seriously?” Lykoi’s glare said it all.
“I have informed Oracle that we found the missing students. She informed me that the GPD eta is ten minutes.”
“Good, that will give us time to search the premises for anything odd.” Nightwing states.
“Way ahead of you,” Red Hood shouts from afar. Eyes rolls but they all shrug in the end.
“What do you mean there weren’t any prints or such leading to the student’s kidnapper?” Commissioner Gordon asks, well he yelled but his face isn’t red yet, as the faces the Bats (aside from the large bat himself) and the Miraculous Team.
“What he meant to say, was that nothing in this warehouse suggested that there was third person let alone a typical Gotham’s villain.”
“So, you're saying this was an act?”
“No, I don’t think all of it was an act?”
“Hmm… This isn’t going to go well with explaining this to GA’s headmistress.”
Ladybird might as well say goodbye to her life and curl next to Robin in her final moments. If this was just a fake, Lila and anyone who was involved with this plan of hers are in for a treat and she’ll have front row access to it.
“Just make sure that girls are returned to GA safely, Gordon,” Nightwing instructs, they knew what he was going for. It was to them out of her and on patrol—well some of them at the very least.
~*~
Marinette curls into Damian’s chest, looking at the screen in front of them. After a night like that she didn’t want to think about the consequences that the liar had unleashed.
“You okay?” Damian presses his lips against her forehead, their hands intertwine fighting for dominance.
Marinette doesn’t say anything. How could she? There was so much floating around her mind that she couldn’t place what she was feeling at the moment.
They stay in silence until a loud thud disrupts the environment.
“Bad news,” Dick and the rest of the family file in. “Rossi confessed to the kidnapping being a ploy.”
“Goddammit, there went my morning and quite possibly my entire week.” Marinette groans collapsing next to Damian and covering her face with her hand.
“Well it’s not liked your exchange program can get any worse. You have like three weeks left of it anyway.” Jason shrugs trying to make the mood lighter… it didn’t help.
“Not now, Jaybird,” Marinette growls, causing the hairs on the back of everyone’s neck to raise high. It was rare to see Marinette angry and Lila has done the impossible. Kwami may help in the morning, especially when Marinette doesn’t get her coffee.
~*~
Mari Needs Coffee @MarinetteMemes
Is it too late to push someone off the roof of WE? 🤔 #shemesswiththewrongsgirl #ineedcoffee
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Some tips for recruitment season for Computer science students based on my experience.
Note: This is mostly for 1st and 2nd year students. Here is what I did to get my first internship offer.
1. Focus on your resume.
Before you even start applying to jobs, make sure that your resume has the following:
uses a basic template that is easily readable by the ATS. example
includes a Projects section!! this one is very important. You can include projects that you did in your class, in any CS clubs or something that you did on your own.
(optional but good to have) any job experience even if it is not related to cs or engineering + any clubs you are part of or hold leadership positions in.
Note: Think of your resume as a questionnaire. The interviewers will interview you based on what you put on your resume. The more technical projects and experience you showcase, the more you can stand out.
2. Work on some side projects if you don’t have any yet. You can look up tutorials on YouTube on how to make a website (both front end + backend). I recommend code academy, udemy, coursera or edx courses. Learn flutter+dart to make a mobile app. Be able to use java, python and c++ (be confident in at least one language).
3. Start applying to jobs! Cover letters are mostly optional so don’t worry about them too much.
attend your college career fair and talk to recruiters. Ask for their email so you can contact them and send them a thank you message + stay connected. Getting in touch with recruiters is key.
here is a github database of multiple internships to appy for.
reach out to recruiters and alumni on linkedin. try to get referrals.
Note: even if you don’t think you are qualified for an internship, APPLY ANYWAY.
Now you wait for the interviews. Getting an interview is the hardest part :( BUT YOU GOT THIS. Keep applying and networking.
4. Most internships don’t really ask for a technical interview if you are a 1st or 2nd year student. But leetcode is the best place to prepare for technical interviews. Here are some problems to get you started. But besides that make sure you can clearly explain the projects on your resume and maybe even walk the interviewer through your thought process and any issues you had!
5. Time for behavioral interview which is the last final step. Here are some commonly asked interview questions. In a word document try to come up with a situation where you faced the issues described in these questions and then write them down. Also write down how you solved the issues. This is how you will prepare for the interview. Try to memorize the scenarios but also make sure that you speak naturally during the interview lol. They don’t need to know you memorized it. Smile and be pleasant during the interview! Everyone loves happy people!! Always project yourself in a positive light.
Example: Tell us about a time you missed a deadline.
Answer: taken from this website
situation/task - I was once given a deadline to produce an article for a client on a short turnaround time. I believed I could handle the article in addition to the workload I already had, but I miscalculated how long it would take me to write it. The morning the article was due, I realized I would not make it in time and contacted my boss to explain the situation.
action - I apologized, explained what happened and asked for an extension, which he granted.
result - I learned that I need to be honest with myself about the workload I can handle each day. I also learned that when accepting assignments, I need to include a time buffer to ensure that even if unforeseen events arise, I am able to meet my deadlines.
Note: If they ask for a weakness, mention something that is not your job related. For example, you can say something about creativity being your weakness when you are applying for a technical role. Make sure that you also mention what you are doing in order to improve the skill you said you are weak in. In this case, it could be taking a creative writing class etc.
6. Always have questions to ask at the end of the interview. Ask about any doubts you may have regarding the work. Ask if there is any specific technology you need to learn in advance. Ask how the day to day work life would look like. Ask how the company has been dealing with COVID. Ask them to describe a successful intern etc.
7. Send a thank you email to the recruiter and the interviewers! Don’t forget this one!
Lastly, keep working hard and be open to constructive criticism. Have other people look over your resume. Do NOT compare yourself with others. You are competing with YOURSELF during the recruitment process. Believe in yourself and all the work you have put in so far. Accept the fact that the recruitment process is stressful and find healthy ways to cope with stress. Most importantly, be nice to others and do not put other people down during this time :) You got this!! I believe in you. It is never too late to apply. There are internships all year round so do not worry :)
hello ! im gonna pursue data science and i saw that we'll learn some coding in it so i just wanted to know ,, is coding very difficult?? do we need math for it ??
hi!
I’ve been working as a data scientist for 2 years, and I should probably note that I work at a traditional/non-tech company, I’m sure data scientists at tech companies have a very different experience
I majored in math in college and I got a masters in statistics, and I took only 2 courses in that time fully dedicated to coding, one was in C++ and the other was in SAS. several of my upper-level undergrad courses and all of my masters-level courses used some MATLAB, SAS, or R. I taught myself the basics of SQL and Python (mainly pandas and scikit-learn, two critical Python libraries for data science) before I applied for jobs because they came up a lot in job descriptions. I mentioned 6 coding languages there, but actually the only coding languages in my day-to-day work are SQL and Python, which I mostly taught myself
as you can see from this blog I’m not exactly a newbie to coding, and I remember coding CSS and HTML as early as age 10 or 11, so my experience may not be universal, but I don’t think coding is hard. in fact, coding will probably end up being your favorite part of your job as a data scientist. it beats attending meetings, preparing slides, writing emails, and (the worst of all personally) updating documentation
but math is one of the fundamental skills you will need as a data scientist, so just because you don’t necessarily need it for coding, you will probably need it for developing models, validating your models, and calculating key performance metrics
when I’ve interviewed candidates in the past, most will have a plethora of coding languages on their resume, but I’m only really looking for them to have a good grasp of SQL and Python if they have those on their resume. the thing that is harder to teach is the probability and machine learning theory
I hope I answered your question, sorry I probably wrote too much, but I enjoyed answering, thanks :)
Linguistics Jobs: Interview with a Product Manager
A lot of tech people I know say “the best skill a programmer can have is knowing how to look up the right answer on Stack Exchange” It’s one of those websites that people use every day, but perhaps without thinking about how it gets built. Megan Risdal is one of the people who make Stack Overflow happen, as a Product Manager leading Public Q&A. As Megan mentions below, there’s even a Linguistics Stack Exchange (you might just see some old answers from me there). Megan has not only forged a career for herself in tech, she helps demystify the industry for other linguists who might follow in her footsteps, on Twitter (@MeganRisdal) and her blog.
What did you study at university?
My undergraduate degree is in Psychology from the University of Wisconsin, Eau Claire where my interests were in individual differences. I also did a minor in French and this is where I first learned about linguistics as a field of study. My combined interests in language and individual differences psychology led me to completing a senior thesis project on variation in attitudes towards linguistic diversity. Just last year this work was published with my then advisor, Dr. Erica Benson, as a chapter in Language Regard: Methods, Variation, and Change.
From here, I did a Master's degree in Sociolinguistics at North Carolina State University. Building on my statistics background from studying psychology, I dove deeper into quantitative methods, learning R along the way, while focusing on sociophonetics and laboratory phonology. For my capstone project, I measured articulatory (ultrasound tongue imaging), aerodynamic, (nasal/oral airflow), and acoustic variation in coarticulatory vowel nasalization strategies among Anglo-American and African American (Vernacular) English speakers.
Finally, I started a PhD at UCLA where I intended to continue studying laboratory phonology. I only ended up finishing one year which was spent on theoretical foundations, articulatory phonetics, and learnability before leaving with a second Master's degree in Linguistics. I ended up deciding to leave academia because I was disillusioned already with the prospect of the job market and the limited potential for my work to have impact beyond academia. I made my mind up when I applied for a job at Google and got an interview. I ultimately failed, but this was enough for me to feel confident my resume was "good enough" (completely incidentally I ended up later getting hired and working at Google for a couple of years prior to my current role).
What is your job?
For the past six months I've been working as a Product Manager at Stack Overflow where I lead the team working on public Q&A. If you're not familiar with Stack Overflow, it's a site where anyone who codes can come to find answers to their programming questions. We also have the Stack Exchange network which has similar Q&A sites for other topics like cooking and anime. There's even a Linguistics Stack Exchange site.
In my day-to-day, as a product manager, I work closely with our developers, designers, researchers, data scientists, community managers, marketing, and leadership. So, it's a lot of meetings and a lot of Google Docs. My job entails taking many, many inputs and synthesizing them into a strategy and product roadmap that the team executes on to make Stack Overflow a more useful, engaging place for all developers. On a given day, you could catch me writing a new feature specification for a developer, reviewing results of an experiment with our data scientists, or dropping in on user interviews. One of the things I love the most about my job is the variety. If a project is slipping or we just don't have the resources for something important, I'm the person who can step in and do what it takes to make sure the work of my collaborators adds up to something successful.
How does your linguistics training help you in your job?
My training in linguistics absolutely helps me.
First, and most importantly I believe, my background in sociolinguistics has taught me the significance of diversity among groups of people (like users of a product) in so many ways. For example, Stack Overflow sees many millions of users every month, but we know that not everyone is equally likely to participate on the site. There are huge, intimidating barriers to participation which disproportionately impact different groups of people depending on things like their background and experience coding. So every day I think about how changes to the product will affect different types of users. Me and my team are constantly striving to better understand the important ways our users vary in their backgrounds, motivations, and pain points and how we can better meet their needs. Especially in a globally diverse online community like ours where users interact and community with each other it's extremely important for me and my colleagues to think about always.
Second, and more concretely, the quantitative methods and experimental best practices I acquired while studying linguistics are highly applicable to my day-to-day job. We make use of a lot of different qualitative and quantitative research methods at Stack Overflow and having training in this area allows me to leverage these resources effectively in my product decision-making. Before I joined Stack Overflow, I had also spent some time as a data scientist, so my background in statistics and R was extremely relevant there. Without this training, I don't think I would be where I am today.
Do you have any advice do you wish someone had given to you about linguistics/careers/university?
Overall, I'm very happy with my trajectory. I'm extremely grateful to everyone who supported me at every stage and I would not be where I am today without all of these experience (yes including dropping out of a PhD!). That said, some thing that I wish I had encountered sooner are:
Seriously, build a public portfolio. Make your work visible. Curate an online presence. Having even a just a modest Twitter following and some publicly discoverable content with my name on it has helped me immeasurably in my career. Oh, and learn git.
Pay some attention to what's going on outside of your academic bubble. I fully intended to stay in academia when I started my PhD at UCLA. Had I thought somewhat ahead of time about the possibility that I would end up industry, I may have prioritized different classes or perhaps even chosen a different PhD program altogether. For example, if you have a choice between learning OCaml and Python, maybe see what non-academia has to say, too, as an input to your decision. Then again, hindsight is 2020. I would have seriously regretted not taking statistics/research methods under any circumstances, though.
Any other thoughts or comments?
I think every tech company should look to hire people trained in linguistics. There are so, so many ways in which a background in linguistics is relevant to so many careers in tech. From user research to data science to (apparently) product management, a background in linguistics adds a unique and valuable perspective. If you're not sure what you're qualified for, carefully tailor your experience, cast your net wide, and seek out advice!
More from Megan
Twitter @MeganRisdal
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Recently:
Interview with a Communications Specialist
Interview with a Learning Scientist
Interview with a Lexicographer
Interview with a Journalist
Interview with a PR Consultant
Check out the Linguist Jobs Master List and the Linguist Jobs tag for even more interviews
