Tools in Data Science - Jan 2026#
Tools in Data Science is a diploma level data science course at IIT Madras.
It bridges the gap between theory and real-world implementation. Specifically: you’ll learn what tools do data scientists actually use and how.
It prepares you for AI. AI is rapidly changing how data science work. You’ll practice using AI to learn, execute, and explain data science tasks.
AI will teach you. We give you challenges. You learn by yourself, using AI & humans. Self-learning is part of the course skills.
AI will evaluate you. Since results vary each run, learn to answer them robustly. LLM decisions are final.
There is no course content. Just challenges for you to solve, and prompts to guide you.
Anyone can audit this course. It's public.
Anyone can access this course content for free and submit assessments.
Those auditing can use GitHub notifications and watch activity on the course repository.
Enrolled IITM students can additionally participate in Discourse, get projects evaluated, take the final end-term, and get a certificate.
You MUST know Python, JavaScript, APIs, etc.
You need a good understanding of Python, JavaScript, HTML, APIs, Excel, ChatGPT, and data science concepts.
Take the Entrance Exam. IITM BS students scoring below 40% shouldn’t register for this course (unless there’s no choice).
It's a practical course. Just get it done. "How" matter less.
The course models real-life. Unclear problems, messy data, ridiculous deadlines, limited support.
Find your own unique ways of solving the problems. There’s no one right approach.
It's a hard course. Take it in your last IITM BS Diploma term.
It’s good for learning, maybe not for grades.
Here’s students’ feedback from past terms:
- It used to be an easy course until 2024. # # #
- Now it’s hard and covers more. Take it in your last semester if possible. # # #
- Plan extra time. It takes more time than typical 3-credit courses. # # #
- LLMs grade you – unpredictably. # #
- The ROE is hard. #
- Should you take Tools in Data Science this term? (Ans: take it in your last term)
Take Graded assignment 1 to check if you’re ready for this course. Please drop this course (do it in a later term) if you score low. It’ll be too tough for you now.
But the learnings may be worth the effort.
- May 2025 feedback indicates that students know it’s hard – and still rate the learning high.
- Jan 2025 course experience and farewell post.
Copying & ChatGPT are encouraged.
You CAN copy from friends and AI. In fact, it’s part of the curriculum.
Work in groups. You can use the Internet, WhatsApp, ChatGPT, your notes, your friends, your pets…
Share code. Even in projects, assignments, and exams (except the final in-person end-term exam).
- Why copy? Because in real life, there’s no time to re-invent the wheel. You’ll be working in teams on the shoulders of giants. It’s important to learn how to do that well.
- To learn well, understand what you’re copying. If you’re short of time, prioritize.
- To learn better, share what you’ve learnt. Learn from others’ feedback.
Check system requirements.
Check system-requirements.md for permissions you need, software to install, and websites to access. You may need to speak with your system administrator for access.
8 modules in 12 weeks#
The course covers the typical data science workflow:
| Content | Assessment | Weight | Release Date | Submission Date |
|---|---|---|---|---|
| Entrance Exam | EE | 0% | Wed 07 Jan 2026 | Mon 02 Feb 2026 |
| Graded Assignment (GA) | Best 5 of 8 | 20% | ||
| Setup | GA1 | Fri 06 Feb 2026 | Wed 18 Feb 2026 | |
| Deploy | GA2 | Fri 13 Feb 2026 | Sun 22 Feb 2026 | |
| Source | GA3 | Fri 20 Feb 2026 | Sun 01 Mar 2026 | |
| Wrangle | GA4 | Fri 27 Feb 2026 | Sun 08 Mar 2026 | |
| Analyze | GA5 | Fri 06 Mar 2026 | Fri 20 Mar 2026 | |
| Test | GA6 | Fri 13 Mar 2026 | Sun 22 Mar 2026 | |
| Present | GA7 | Fri 20 Mar 2026 | Sun 29 Mar 2026 | |
| Package | GA8 | Fri 27 Mar 2026 | Wed 08 Apr 2026 | |
| Project 1 | P1 | 20% | Wed 11 Feb 2026 | Mon 30 Mar 2026 |
| Project 2 | P2 | 20% | Fri 6 Mar 2026 | Mon 13 Apr 2026 |
| Remote Online Exam (hard) | ROE | 20% | Sun 05 Apr 2026 | Sun 05 Apr 2026 |
| Final end-term (in-person) | F | 20% | Sun 10 May 2026 | Sun 10 May 2026 |
Notes
- We may post bonus activities on Discourse. See previous bonus activities
Resources#
| Resource | IITM | Public |
|---|---|---|
| Live Video Sessions | Recordings | YouTube / Archives |
| Discussion | IITM | Public |
| Course page - Jan 2026 | IITM | Public |
| Announcement group - Jan 2026 | IITM | Public |
| Grading Document - Jan 2026 | IITM | |
| Student Handbook | IITM |
Contacts#
| Role | Name | Discourse | |
|---|---|---|---|
| Faculty | Anand S | [email protected] | @s.anand |
| Instructor | Carlton D’Silva | [email protected] | @carlton |
| Instructor | Prasanna S | [email protected] | @iamprasna |
| Teaching Assistant | Hritik Roshan Maurya | [email protected] | @HritikRoshan_HRM |
| Teaching Assistant | Jivraj Singh | [email protected] | @Jivraj |
| Teaching Assistant | Mayank Poddar | [email protected] | @23f3004197 |
| Teaching Assistant | Sujal Pradhan | [email protected] | @23f2004759 |
What to contact whom, for what, and how:
- Teaching assistants: To learn the subject after asking AI twice. E.g. “How do I solve this assignment / project”
- Unstructors: For exceptions after asking AI, TAs, and with proof. E.g. “My marks are wrong”, “I need an extension”, etc.
- Faculty: For suggestions on next term’s course content.
We used to have a Virtual TA (a custom GPT) who has retired now.
Check communications#
Check these three links regularly to keep up with the course.
- Seek Notifications for Course Notifications. Log into seek.onlinedegree.iitm.ac.in and click on the bell icon on the top right corner. Check notifications daily.
- Your email for Course Announcements. Seek Inbox are forwarded to your email. Check daily. Check spam folders too.
- TDS Discourse: Faculty, instructors, and TAs will share updates and address queries here. Email [email protected] cc: [email protected] if you can’t access Discourse.