Live mentor-led classes
With recordings for revision
24-hour doubt resolution
Community channel + weekly office hours
Certificate + LinkedIn badge
On completion from Grow2Grab
Online or in Jalandhar
Live batches for learners across India
Course Overview
A build-focused course, not a prompt-writing workshop
This programme is about making applications on top of large language models. You learn how LLMs work, how to fine-tune open models, how to store and search your own documents with vector databases, and how to connect it all with LangChain, LlamaIndex and MCP.
Prompt engineering is part of it, but it is one tool among several. The course is listed at intermediate level, so it moves faster than a general AI awareness class.
What it is
- ✓Hands-on, with a capstone Generative AI product
- ✓Live sessions with mentors, plus recordings
- ✓Focused on RAG, vector search, agents and fine-tuning
What it is not
- ✕A first course in programming
- ✕A general introduction to ChatGPT features
- ✕A guarantee of a job or a salary
What you will learn
Five modules, 62 lessons, one capstone
The curriculum below is the module structure on Grow2Grab's current Generative AI training page.
LLMs and fine-tuning
- How LLMs work (GPT, Claude, Gemini)
- Prompting: system prompts, few-shot, chain-of-thought
- LoRA and QLoRA fine-tuning of open models
- Dataset preparation and RLHF basics
Vector databases and hybrid search
- Embeddings and semantic search
- Vector stores such as Pinecone, Weaviate and Chroma
- Hybrid search
RAG pipelines
- Retrieval-augmented generation end to end
- Multi-document question answering
LangChain, LlamaIndex and MCP
- LangChain chains and agents
- LlamaIndex data connectors
- Tool use and function calling
Capstone: a Generative AI product
- Plan, build and present a working GenAI application
- Reviewed by your mentor
Grow2Grab's Jalandhar course page also lists CrewAI, LangGraph, n8n automation and Next.js deployment among the topics. Agents are covered in depth in the separate AI Agents course.
Practical Work
What you will build
These are the outcomes listed on Grow2Grab's course page. You finish with work you can put on GitHub and explain in an interview.
RAG
A RAG chatbot
Answers questions from your own documents using embeddings, a vector store and retrieval. Shows you can ground a model in real data.
Fine-Tuning
A fine-tuned open model
Adapt an open-source LLM such as Llama or Mistral with LoRA or QLoRA. Shows you can customise a model, not just call an API.
Agents
An agent with tools
An agent built with LangChain that calls tools and APIs to complete a task. Shows multi-step reasoning and tool use.
Capstone
A Generative AI product
The final module: design, build and present one complete application with your mentor's review.
Why Grow2Grab
What you get with the programme
Live mentor sessions
Classes with Q&A, and recordings if you miss one.
Doubt resolution
A dedicated community with 24-hour doubt resolution and weekly mentor office hours.
A company that builds AI
Grow2Grab Infotech also develops AI systems for clients. See our AI services
Projects for your portfolio
Work you can add to GitHub and discuss in interviews.
Certificate and LinkedIn badge
Issued on completion of the programme.
Career support
Resume reviews, mock interviews and referrals. This is support, not a guarantee of a job.
Duration, Format and Fee
The practical details
Course Fee
₹20,000 – ₹40,000
This is the range on Grow2Grab's current course page. The fee depends on the track and batch, and EMI options are listed.
Ask for the exact fee, what it includes and payment terms in writing before you enrol.
Learning Outcomes
What you will be able to do
These are skills you practise during the course. Whether they lead to a particular job or income depends on your effort and the market, and Grow2Grab does not promise either.
FAQ