Many graduating students across India are faced with the same big decision. The first path forward is the BTech in Computer Science and Engineering. Having launched IT in India over the last thirty years, this programme is the safe and trusted option for many. The second path is the BTech in CSE with AI and ML. This is the new and rapidly advancing path, and the options with this programme are endless, as AI and ML are the technologies that are changing and reshaping industry across the globe.

Just a few years ago, AI was smuggled away into the secret research labs of big companies like Google or left to the pages of a lengthy and convoluted PhD thesis. Fast forward, and even interns at mid-sized start-ups in Gurugram are expected to be fluent in the language of AI and ML when assessing and optimising embedding search pipelines. The gap between industry and academia closed in the blink of an eye.

It’s not just tech companies leading this. AI in healthcare is diagnosing illnesses in scans. Financial technology is performing fraud detection across billions of transactions every second. Self-driving cars are changing the entire field of automotive engineering. Defence is developing smart surveillance. Each of these fields has an immediate shortage of engineers who can understand systems and intelligence. India, in particular, has an amazing opportunity and a deadline.

The government’s INDIAai Mission has committed ₹10,000 crore to build AI infrastructure and talent. AICTE has mandated AI integration into engineering curricula under NEP 2020. The signal from the top could not be clearer. But policy creates opportunity, not capability. Capability comes from four years of dedicated, well-designed education — the kind that doesn’t treat AI as a module tacked onto a traditional CS degree, but as the entire orientation of the programme.

Another thing to consider is the maturity of the degree on offer. A traditional BTech CSE degree has around forty years of industry certainty. Meanwhile, BTech in AI & ML will take longer to establish a sustained alumni network and long-term employment data. Programmes running in universities like The NorthCap University (NCU) are closing this gap as we speak, but it is worth mentioning. The automation of all industries using intelligent systems is not a theory. The transformation is already a reality. Engineers graduating in 2028–2030 will be the ones who are engaged to build, implement, operate, and evaluate these systems. The level of preparation that these engineers will have hinges mainly on the decisions that are made in the present. These decisions will mainly be which degree to pursue and at which institution.

If you have been wondering which institutions are actually delivering on the promise of AI engineering — not just rebranding old syllabi — The NorthCap University (NCU), Gurugram, is one of the clearest answers in northern India. NCU has architected its BTech CSE with Specialisation in AI & ML to be industry-led, research-backed, and globally certification-aligned from the ground up.

Why is NCU one of the preferred choices?

1. An AI lab that is actually world-class: The Intel Unnati AI Lab gives students hands-on exposure to real-world AI development and deployment with high-end, scalable infrastructure, so that students get hands-on experience of building projects based on real-world applications.
2. Honeywell Centre of Excellence: In collaboration with ICT, it adds an industry-mentored research layer, connecting students to live automation and AI-driven industry challenges.
3. Global certifications built into the curriculum: Through a strategic partnership with Certiport, students pursue globally recognised certifications, including Microsoft Azure AI-900, Pearson Generative AI Certification, and AWS AI credentials — not as optional add-ons but as woven-in milestones of the degree. Employers see these credentials on Day 1 of placement season.
4. Curriculum co-designed with industry & IIT faculty: The AI & ML programme is not written in an ivory tower. It is continuously revised by industry experts and academicians from IITs and JNU, ensuring that what students learn in Semester 5 reflects what companies actually need in the hiring year — not what they needed five years ago.
5. Real industry mentorship, not mock projects: Students at NCU work on live projects of real organisations under the direct mentorship of both a faculty member and an industry professional. Industry mentors visit campus, conduct pre-placement interviews, and stay associated through the student’s journey — creating a professional network before graduation.
6. A pathway for curious minds who want more: NCU faculty actively mentor students towards patents, research publications, and PhD pathways. For students who discover that their appetite goes beyond a job and want to build the next frontier, the research culture is already there, with active PhD programmes in AI/ML and medical imaging AI.

Institutions like NCU are not just following that trend. They are building the curriculum, the labs, the industry connections, and the research culture to make sure their graduates arrive fluent — and then some.

The question is not whether to learn AI. The question is whether to spend four years doing it properly.

Author
Dr. Meghna Sharma
Associate Professor & Associate Head
Lead, AI & Machine Learning Specialisation
Department of Computer Science and Engineering
The NorthCap University, Gurugram
https://www.linkedin.com/in/ meghna-sharma-a87a6436/
Broad Research area: Artificial intelligence and machine learning