The half-life of technical knowledge keeps shrinking, and AI is the sharpest example. The most valuable professional habit isn't knowing today's tools — it's building a system for continuously learning the next ones. That conviction is why I took on an eighteen-month Major in Artificial Intelligence at IIT Ropar, run with NSDC and Masai, and read it in parallel with my core engineering degree rather than after it.
Depth on purpose, not by accident
It's easy to pick up AI in fragments — a course here, a tutorial there — and end up with a patchy, self-assembled understanding. I wanted the opposite: a structured, sustained, formal grounding in the field, long enough and rigorous enough to build real depth rather than familiarity.
Choosing an eighteen-month program is a deliberate bet that depth compounds. Fragmented learning gives you the ability to use a tool; formal depth gives you the ability to understand why it works, which is what lets you adapt when the tool changes — and in AI, it always changes.
Why parallel, not sequential
- Parallel learning forces integration. Reading the AI major alongside the engineering core meant the two constantly informed each other, instead of sitting in separate mental boxes. Applied understanding beats sequential memorization.
- It's a statement about time. Doing two demanding tracks at once is a commitment to using the window you have fully, rather than deferring the harder investment to "later."
- It builds the muscle that actually matters. The specific models will date. The capacity to absorb a rigorous technical field while already carrying a full load — that's the durable, transferable skill.
The takeaway
The professionals who stay valuable over a career are the ones who treat learning as a permanent, structured part of the job, not a phase that ends with a degree. Committing to a formal AI major in parallel with my engineering core was my way of building that discipline early — depth on purpose, sustained over time.
The full context of the program is on the page below.
👉 Read it: www.divyakush.com/insights/iit-ropar-major
Divyakush Punjabi — Full-Stack & AI Systems Engineer
🌐 https://www.divyakush.com · 💼 LinkedIn · 💻 GitHub
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