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. ...
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! ...
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 ...
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? ...
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? ...
Arun Tangirala and I webinared on “AI in Education” yesterday." “(“Webinared” is not a word. But “verbing weirds language”.)” Mid-way, Jose Swan from the audience asked, “Can you summarise this session using an AI? There are SEVERAL tools you can use to summarize talks. Whisper for transcription, FFMpeg for keyframe extraction, #NotebookLM for podcast generation, text-embedding-3-small for topic modelling, and of course, any regular LLM include #ChatGPT for summarization or translation. ...