Here’s my address to the graduating class the IITM BS Program today: Make five new friends today. Your CGPA is what you’re most focused on. When I graduated, my CGPA helped me get a job. It didn’t help much after that. Getting that job helped me for the four years I worked there. That’s it. The things I learnt in class helped a bit longer. Maybe six years. There is a long tail. ...
At 2 pm IST today (Fri 12 Jun 2026), I’m running a workshop at Paradox, IITM - at DOMS 101. You can join online at https://meet.google.com/cpt-faee-ucx and ask questions on chat. Agenda: You’ve been told AI can pass your exams. But what happens when you actually watch it try — live, on your questions, in real time? This workshop starts with a collective experiment: we ask coding agents to solve real exams (including IITM exams) and see how it solves them. ...
On Sat 13 Jun 2026 at 3 pm, I’m conducting an online workshop on “Data Stories with AI”. Register at https://forms.gle/dNkUxtJ2PVqNMNcE9 In this workshop, you will use ChatGPT and Claude, mostly, to: Find data Analyze it Extract insights Visualize as stories It’s a data visualization using AI workshop for journalists - but you don’t need to know data, visualization, journalism, or even technology. But this is a practical workshop. You’ll be doing stuff and sharing your results. ...
Tools in Data Science has a remote online exam (ROE). It has a tough reputation. We conducted one today. Here’s how today’s ROE unfolded. The TAs had created 13 questions and shared it with me yesterday. This morning, I tried solving them. At first glance, it looked scarily hard! But I just jumpted down a few questions, and found that five questions were trivial, i.e. I just used the “Ask AI” button to copy the question into ChatGPT and it gave me the answer. ...
I researched the AI policies across 25 universities. In the last 6 months, I conducted sessions at three of these Universities: IIT Madras, Singapore University of Technology and Design, and Ashoka University. Interestingly, these are the three lowest ranked universities in my analysis of AI policies. This is where I’m glad that correlation does not imply causation.
TDS Project 1 wasn’t just a student project. It was a research and social experiment, too. We tested two skills - analytics and design. The design tests were diverse – and students fared worse there. Design may matter more in the AI era, and I’m glad some designs are brilliant. (But not diverse/creative enough.) I also learnt that Gemini beats Midjourney, which beats ChatGPT for image generation. I asked them to contribute to open source. Most PRs were trivial. But five students made a real difference. For example, this PR to Marimo is excellent! ...
Terence Tao said, “We haven’t done many experiments … large-scale studies where we take a thousand problems and just test them.” So I told Claude: You know my style. Suggest some innovative experiments I could run. The first suggestion was cool! The Polya Audit. Polya’s How to Solve It lists 20 heuristics (work backwards, induction, analogy, etc.). Mathematicians treat these as wisdom. Nobody has ever measured which ones actually work, and on what problem types. ...
I’ve been using AI in my Tools in Data Science course for over two years - to teach AI, and using AI to teach. I told GitHub Copilot (prompt) to go through my transcripts, blog posts, code, and things I learned since 2024 to list my every experiment in AI education, rating it on importance and novelty. Here is the full list of my experiments. 1. Teach using exams and prompts, not content ⭐ Use exams to teach. The typical student is busy. They want grades, not learning. They’ll write the exams, but not read the content. So, I moved the course material into the questions. If they can answer the question, great. Skip the content. Use AI to generate the content. I used to write content. Then I linked to the best content online – it’s better than mine. Now, AI drafts comics, interactive explainers, and simulators. My job is to pick good topics and generate in good formats. Give them prompts directly. Skip the content! I generated them with prompts anyway. Give students the prompts directly. They can use better AI models, revise the prompts, and learn how to learn with AI. ⭐ Add an “Ask AI” button. Make it easy for students to use ChatGPT. Stop pretending that real-world problem solving is closed-book and solo. ⭐ Make test cases teach, not just grade. Automate the testing (with code or AI). Good test cases show students the kind of mistake they may - teaching them, not just grading them. That’s great for teachers to analyze, too. Test first, then teach from the mistakes. Let them solve problems first. Then teach them, focusing on what failed. AI does the work; humans handle what AI can’t. This lets us teach really useful skills based on real mistakes. 2. Make cheating pointless through design, not detection ...
Given how easy it is to create interactive explainers with LLMs, we should totally do more of these! For example, I read about “Adversarial Validation” in my Kaggle Notebooks exploration. It’s the first time I heard of it and I couldn’t understand it. So, I asked Gemini to create an interactive explainer: Create an interactive animated explainer to teach what adversarial validation is. Provide sample code only at the end. Keep the bulk of the explainer focused on explaining the concept in simple language. ELI15 ...
Yesterday, I was part of an IIM Bangalore interview panel at Hyderabad, along with Professor Subhabrata Das and Debajyoti. Panels typically comprise of two faculty and an alumni, and handle 8 interviews in the morning and eight in the evening, though in our case, we had 9 each. As we arrived, we were given a USB drive with the student’s resume, statement of purpose, and other documents that they had submitted, which included employment contracts, declarations, letters of recommendation, etc., depending on the student. Each interview was approximately 20 minutes. Luckily, Dr Das set a timer for 18, so we didn’t go too far beyond. ...
An effective way to solve online exams is to point a coding agent at it. I use that on my Tools in Data Science course in two ways: As a test case of my code. If my agent can solve it, good: I set the question correctly. As a test of student ability. If it can’t, good: it’s a tough question (provided I didn’t make a mistake). For PyConf, Hyderabad, my colleague built a Crack the Prompt challenge. Crack it and you get… I don’t know… goodies? A job interview? Leaderboard bragging rights? ...
I often research how the world will change with AI by asking AI. Today’s session was informative. I asked Claude, roughly Economics changes human behavior. As intelligence cost falls to zero, here are some changes in my behavior [I listed these]. Others will have experienced behavioral changes too. Search online and synthesize behavioral changes. It said this. 🟡 People spend time on problem framing & evaluation. AI can execute the middle. (I’m OK at this. Need to do more framing + evaluation.) 🟢 People don’t plan, they just build. (I’m prototyping a lot.) 🟢 People build personal data & context. (I’m mining my digital exhaust.) 🔴 People queue work for agents, delegating into the future. (I’m not. I need to do far more of this.) 🟢 People shift from searching to asking for answers. (I do this a lot, e.g. this post.) 🟡 People are AI-delegating junior jobs and developing senior level taste early. (Need to do more.) 🟡 People treat unresolved emotions as prompts. (Need to do more.) Rough legend: 🟢 = Stuff I know. 🟡 = I kind-of know. 🔴 = New learning. ...
People worry that AI atrophies skills. Also that junior jobs, hence learning opportunities, are shrinking. Can AI fill the gap, i.e. help build skills? One approach is: Do it without AI. Then have AI critique it and learn from it. (Several variations work, e.g. have the AI do it independently and compare. Have multiple AIs do it and compare. Have AI do it and you critique - but this is hard.) ...
After an early morning beach walk with a classmate, I realized I hadn’t taken my house keys. My daughter would be sleeping, so I wandered with my phone. This is when I get ideas - often a dangerous time for my students. In this case, the idea was a rambling conversation with Claude that roughly begins with: As part of my Tools in Data Science course, I plan to create a Cloudflare worker which allows students to play a game using an API. The aim is to help them learn how to build or use AI coding agents to interact with APIs to solve problems. ...
In my graded assignments students can pick an AI and “Ask AI” any question at the click of a button. It defaults to Google AI Mode, but other models are available. I know who uses which model and their scores in each assignment. I asked Codex to test the hypothesis whether using a specific model helps students perform better. The short answer? Yes. Model choice matters a lot. Across 333 students, here’s how much more/less students score compared with ChatGPT: ...
I use comics to make my course more engaging. Each question has a comic strip that explains what question is trying to teach. For example, here’s the comic for the question that teaches students about prompt injection attacks: For each question, I use this prompt on Nano Banano Pro via Gemini 3 Pro: Create a simple black and white line drawing comic strips with minimal shading, with 1-2 panels, and clear speech bubbles with capitalized text, to explain why my online student quizzes teach a specific concept in a specific way. Use the likeness of the characters and style in the attached image from https://files.s-anand.net/images/gb-shuv-genie.avif. 1. GB: an enthusiastic socially oblivious geek chatterbox 2. Shuv: a cynic whose humor is at the expense of others 3. Genie: a naive, over-helpful AI that pops out of a lamp Their exaggerated facial expressions to convey their emotions effectively. --- Panel 1/2 (left): GB (excited): I taught Genie to follow orders. Shuv (deadpan): Genie, beat yourself to death. Panel 2/2 (right): Genie is a bloody mess, having beaten itself to death. GB (sheepish): Maybe obedient isn't always best... … along with this reference image for character consistency: ...
Graded Assignment 1 (GA1) for the Tools in Data Science course is released and is due Sun 15 Feb 2026. See https://exam.sanand.workers.dev/tds-2026-01-ga1 If you already started, you might notice some questions have changed. Why is GA1 changing? Because some questions don’t work. For example: We replaced Claude Artifacts with a Vercel question because Claude won’t allow a proxy anymore. A question had unintentionally wrong instructions. (Some questions have intentionally wrong instructions, but those are, …um… intentional). Someone changed an API key. … etc. When will GA1 stabilize? Probably by end of day, Sun 9 Feb 2026? ...
This morning, I migrated my Tools in Data Science course page from Docsify to Hugo using Codex. Why? Because Docsify was great for a single term. For multiple terms, archives became complex. I still could have made it work, but it felt like time to move towards a static site generator. I don’t know how Hugo or Go work. I didn’t look at the code. I just gave Codex instructions and it did the rest. This gives me a bit more confidence that educators can start creating their own course sites without needing coding or platforms. Soon, they might not be stuck to LMSs either - they can build their own. ...
Several educators have AI-enabled their courses, like: David Malan at Harvard CS50 provides an AI-powered “rubber duck debugger” trained on course-specific materials. Mohan Paturi at UC San Diego has deployed AI-tutors to his students. Ethan Mollick at Wharton uses AI as tutor, coach, teammate, simulator, even student, and runs simulations. Jeremy Howard’s Fast.ai encourages students to use LLMs to write code, with a strict verification loop. Andrew Ng DeepLearning.AI integrates a chatbot into the platform, next to code cells, to handle syntax errors and beginner questions. But no one seems to have eliminated reading material, nor added an “Ask AI” button to solve each question, nor run it at my scale (~3,000 students annually). ...
My Tools in Data Science course is available publicly, with a few changes from last year. First, I removed all the content! Last year, Claude generated teaching material using my prompts. But what’s the point? I might as well give students the prompts directly. They can tweak it to their needs. This time, TDS shares the questions needed to learn a topic. Any AI will give you good answers. Second, it focuses on what AI does NOT do well. Coding syntax? Who cares. Basic analysis? ChatGPT can do that. In fact, each question now has an “Ask AI” button that dumps the question into your favorite AI tool. Just paste the answer and move on. ...