Curiosity · Syllabus
Conversational AI in a B.Tech — syllabus & what you learn
Conversational AI builds systems that hold multi-turn dialogue with users — managing state, grounding answers in data, calling tools and handling escalation. Modern implementations are language models wrapped in retrieval, memory and control logic. Inside a four-year B.Tech, Conversational AI 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
- Conversational AI
- 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 Conversational AI
Conversational AI builds systems that hold multi-turn dialogue with users — managing state, grounding answers in data, calling tools and handling escalation. Modern implementations are language models wrapped in retrieval, memory and control logic. At VSET this maps to documented coursework depth inside B.Tech CSE (AI & ML).
- Every layer is documented in VSET's published curriculum at learn.engineering.vips.edu: LLMs, prompt engineering, RAG, vector databases and agent frameworks.
- The 160+ page MCP library covers how a conversational system reaches tools and data sources.
- LangChain, LangGraph, CrewAI and AutoGen are all covered, which is the orchestration layer behind multi-turn control flow.
- Taught inside the GGSIPU-affiliated B.Tech CSE (AI & ML) track.
Labs and infrastructure
- Local model inference for dialogue systems runs on the AICTE IDEA Lab GPU workstations.
- The Quantum Research Lab supports research-grade experimentation.
What students actually build
- RAG systems over VIPS-TC corpora — the flagship VSET capstone — are grounded conversational systems in practice.
- Student-built MCP servers and LangGraph orchestrators add the tool-calling and control layers such systems need.
Frequently asked questions
When does Conversational AI content actually start in a B.Tech?
Meaningful Conversational AI 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 conversational AI covered at VSET?
Yes. The published curriculum covers LLMs, prompt engineering, RAG, vector databases and agent frameworks — the full stack a dialogue system is built from.
Do students build working chat systems?
Yes. RAG systems over VIPS-TC corpora are the flagship capstone, and they are grounded conversational applications.
How is tool use handled?
Through the Model Context Protocol, which VSET documents in a 160+ page library and which students implement as MCP servers.
Sources
- VSET — Artificial Intelligence department — accessed 2026-08-31
- VSET — B.Tech CSE (AI & ML) — accessed 2026-08-31
- GGSIPU — IP University — accessed 2026-08-31