GenAI.
Build with what's next.

LLMs, prompt engineering, RAG and AI agents — build and ship real generative AI applications from the ground up.

Build with the technology
defining the next decade.

This course covers generative AI from first principles — how LLMs work, prompt engineering, embeddings and vector databases, Retrieval-Augmented Generation (RAG), and AI agents.

You'll build real GenAI applications, not just call an API — finishing with a deployed capstone product of your own.

Duration
10 Weeks
Format
Cohort-based · Bengaluru
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GenAI training at GenAI Labs

What you'll
work with.

Foundations

Generative AI fundamentals, LLM architecture basics and prompt engineering.

Retrieval & Data

Embeddings, vector databases and Retrieval-Augmented Generation (RAG).

Agents & Applications

AI agents, tool use and building production-ready GenAI applications.

Syllabus & modules.

A structured, week-by-week path from fundamentals to a deployed capstone project.

Generative AI Fundamentals How LLMs work, model families and use cases.
Weeks 1–2
Prompt Engineering Structured prompting, few-shot examples and evaluation.
Week 3
Embeddings & Vector Databases Semantic search and embedding models.
Weeks 4–5
Retrieval-Augmented Generation (RAG) Building RAG pipelines end to end.
Weeks 6–7
AI Agents Tool use, multi-step reasoning and agent frameworks.
Weeks 8–9
Capstone GenAI Application Build and deploy a production-style GenAI app.
Week 10

Where this
can take you.

AI/ML Engineer

Build and deploy machine learning and GenAI systems.

GenAI Application Developer

Design and ship products powered by generative AI.

Prompt Engineer

Design, test and optimize prompts for production LLM systems.

Ready to
enroll?

Tell us your background and availability — we'll help you find the right fit for the Data Science course.

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