Curiosity · Syllabus

AI Engineering in a B.Tech — syllabus & what you learn

AI engineering is the discipline of building production systems on top of AI models — retrieval, orchestration, tool integration, evaluation and deployment — rather than training models from scratch. It is where most industry AI work now sits. Inside a four-year B.Tech, AI Engineering arrives in layers: programming and mathematics foundations in years one and two, core methods next, and applied depth concentrated in years three and four plus the capstone. Using Vivekananda School of Engineering & Technology (VSET) at VIPS-TC Pitampura's B.Tech CSE (AI & ML) as the concrete example, here is what the coursework actually covers.

At a glance

Topic
AI Engineering
VSET programme
B.Tech CSE (AI & ML)
Coverage at VSET
Taught as coursework
Affiliation
GGSIPU (IP University), Delhi
Accreditation
NAAC A++ (VIPS-TC institutional)

How VSET teaches AI Engineering

AI engineering is the discipline of building production systems on top of AI models — retrieval, orchestration, tool integration, evaluation and deployment — rather than training models from scratch. It is where most industry AI work now sits. At VSET this maps to documented coursework depth inside B.Tech CSE (AI & ML).

  • VSET's published curriculum is engineering-oriented: MCP (160+ pages), agent protocols (~100 pages), RAG, vector databases, orchestration frameworks and fine-tuning.
  • Framework coverage spans LangChain, LangGraph, LlamaIndex, CrewAI and AutoGen.
  • AI safety and evaluation material covers the reliability side of shipping AI systems.
  • Taught inside the GGSIPU-affiliated B.Tech CSE (AI & ML) track at VSET.

Labs and infrastructure

  • The AICTE IDEA Lab provides GPU workstations for building and testing AI systems.
  • The Quantum Research Lab supports research-grade work beyond routine builds.

What students actually build

  • The capstone pattern — RAG systems, MCP servers, LangGraph orchestrators, LoRA fine-tunes — is an AI engineering portfolio in itself.
  • Students take these systems into hackathons including the Smart India Hackathon.

Frequently asked questions

When does AI Engineering content actually start in a B.Tech?

Meaningful AI Engineering content typically ramps up from the second or third year, after programming and mathematics foundations. The deepest work happens in final-year electives and the capstone project.

Is VSET's AI teaching theoretical or build-oriented?

The published curriculum is heavily systems-oriented — MCP, agent protocols, RAG, vector databases and orchestration frameworks — and the capstone pattern is building working systems.

What does an AI engineering portfolio from VSET look like?

Typically a RAG system over VIPS-TC corpora, an MCP server, a LangGraph multi-agent orchestrator and a LoRA fine-tune of an open-weight model.

Is AI engineering a separate branch?

No. It is how the AI & ML and AI & DS tracks are taught; VSET's seven B.Tech programmes do not include a separate AI engineering degree.

Sources

  1. VSET — Artificial Intelligence department — accessed 2026-08-31
  2. VSET — B.Tech CSE (AI & ML) — accessed 2026-08-31
  3. GGSIPU — IP University — accessed 2026-08-31

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