GenAI & Agentic AI Engineering Bootcamp in Pune & live online
Two intensive days that cover the full GenAI and agentic AI engineering stack. You run transformer models, work with hosted and local LLMs, build RAG applications, see fine-tuning and quantization in practice, build AI agents with LangGraph, Google ADK and AutoGen, connect them to tools with MCP, and finish with an end-to-end capstone.
ISO 9001:2015
MSME Registered
Startup IndiaSecure payment via Razorpay
After 2 days, you will be able to…
- Explain how transformers and LLMs work, from tokens and attention to next-token prediction
- Use hosted and local LLMs from Python, with prompts, structured output and tool calling
- Build RAG applications with citations, including an offline RAG pipeline
- Explain when to fine-tune or quantize a model, and the trade-offs involved
- Build AI agents with LangGraph, Google ADK or AutoGen, connected to tools through MCP
- Add guardrails and expose an AI application through a FastAPI endpoint
What you'll be able to say“I understand the GenAI stack end to end, and I've built RAG apps and AI agents with it.”
Skills for the roles AI teams are hiring for
We don't promise jobs or salaries. You leave with real skills, your own code on GitHub and a verifiable certificate to show.
Is this workshop for you?
Built for engineering and university students, and open to anyone ready to build with AI.
Engineering students
Any branch, any year. Go beyond ChatGPT and build RAG apps and AI agents you can show in placements and interviews.
MCA, M.Sc. & M.Tech students
Turn LLM theory into working applications, and see the complete GenAI stack in two days.
Software developers
Add LLMs, RAG, AI agents and MCP to your skills in one focused, hands-on intensive.
Data & ML engineers
Connect transformers, fine-tuning and quantization to AI products people can actually use.
Faculty & trainers
An up-to-date, hands-on view of GenAI and agentic AI that you can teach from.
Career switchers
A clear, structured map of AI engineering before you invest months in learning it.
Not sure it's the right fit? Ask us on WhatsApp and we'll tell you honestly.
Every session, in four moves
Live and hands-on: you build every concept yourself, with a mentor beside you.
See it
The mentor builds it live and explains every decision.
Build it together
You code along, step by step, with help on hand.
Build it yourself
A lab where you apply it on your own.
Get feedback
Your work is reviewed so mistakes become learning.
2 days · 12 sessions · 11 hands-on labs
Each session builds on the one before it, and each day ends with something working.
Generative AI Engineering
- Transformer architecture & Hugging FaceLab
- Introduction to neural networks and NLP
- Transformer architecture and self-attention
+5 more topics in the full curriculum
- Large Language Models (LLMs)Lab
- LLM fundamentals and model selection
- Hosted LLMs through third-party APIs
+3 more topics in the full curriculum
- Prompt engineeringLab
- System and user prompts
- Zero-shot and few-shot prompting
+4 more topics in the full curriculum
- LangChain fundamentalsLab
- LangChain architecture and components
- Chat models and prompt templates
+4 more topics in the full curriculum
- Retrieval-Augmented Generation (RAG)Lab
- RAG architecture and workflow
- Document ingestion and parsing
+5 more topics in the full curriculum
Advanced GenAI & Agentic AI Engineering
- Advanced RAG & offline inferenceLab
- RAG pipeline optimization
- Chunking strategies and metadata filtering
+5 more topics in the full curriculum
- Fine-tuning & quantizationLab
- Pretraining vs. fine-tuning
- Supervised fine-tuning fundamentals
+5 more topics in the full curriculum
- Agentic AI fundamentalsLab
- AI agents and agent architectures
- Agents vs. workflows
+5 more topics in the full curriculum
- Agentic AI frameworksLab
- LangGraph: state, nodes, edges and conditional workflows
- Google ADK: agents, tools and orchestration
+3 more topics in the full curriculum
- Model Context Protocol (MCP)Lab
- MCP architecture and core concepts
- MCP clients and servers
+3 more topics in the full curriculum
- Guardrails & responsible AI
- Input and output validation
- Structured-output validation
+4 more topics in the full curriculum
- End-to-end capstoneLab
- Build an enterprise knowledge & action agent
- Integrate an LLM with RAG
+6 more topics in the full curriculum
End-to-end capstone
The last session brings everything together: you build and demo one complete application.
- Build an enterprise knowledge & action agent
- Integrate an LLM with RAG
- Connect tools and external APIs
- Implement an agent workflow
- Integrate selected MCP capabilities
- Expose application endpoints using FastAPI
- Add guardrails, error handling and basic evaluation
- Demonstrate the completed application
See every session and lab
The full curriculum PDF: every topic, the daily schedule and how your work is reviewed.
Industry tools, hands-on
The tools teams use to build AI products. Lab access is provided, so you don't need paid subscriptions.
Code & setup
- PythonThe language for every lab, taught from what you need
AI models
- Hugging Face TransformersLoading and running pretrained transformer models
- OpenAI / Claude / Gemini APIsCalling the leading hosted AI models from your own code
- Local LLMsRunning open models on your own machine, offline
- LoRA / PEFTFine-tuning a model cheaply with adapters
Agent & LLM frameworks
- LangChainBuilding blocks for prompts, chains and tools
- LangGraphAgent workflows with state, routing and human approval
- Google ADKGoogle's Agent Development Kit for building agents
- AutoGenSeveral AI agents working together
- MCPThe open standard for connecting AI agents to tools and data
Data & retrieval
- Vector databasesStoring and searching document chunks for RAG
Apps & APIs
- FastAPITurning your AI code into a real web API
Support before, during and after the workshop
Pre-camp
- Setup on your own laptopVS Code, Python, Jupyter and GitHub with our one-command installer and short videos. vp check confirms you are ready.
- Python primer for AIOnly the Python the workshop uses: variables, lists and dictionaries, functions, loops, files and JSON.
- AI vocabularyA one-page glossary: LLM, token, prompt, API, embedding, agent, RAG.
- Readiness check-insDaily WhatsApp check-in until your setup is green. Stuck? The setup clinic the evening before Day 1 fixes it live.
2 days (intensive), live
- ModeLive online on Zoom, with hands-on labs on your own laptop
- BatchSmall live batches so the mentor can help everyone in labs
- RecordingsSession recordings shared after each day
- Labs11 hands-on labs, with the mentor reviewing your work
Post-camp (7 days)
- Doubt supportWhatsApp support group, our AI assistant for quick answers, and one 45-minute live doubt session on day 3.
- Work submissionSubmit your GitHub link and a 2-minute demo video by day 5. Every submission gets mentor feedback.
- CertificateTwo levels: Participation, and Completion with submitted work. Each has a verifiable link.
- Portfolio kitREADME template, LinkedIn post template, and how to explain your project in an interview.
- AI accessYour personal, capped AI key keeps working for 7 days, so you can keep building.
See what a lab looks like
Real recordings from our hands-on labs: code, running apps and measured results.
A documentation assistant, built end to end
A lab project: FastAPI backend, Chroma vector store and Llama 3 via Groq, answering questions about LangChain documentation.
Measuring answer quality, not guessing
A lab notebook: a local FAISS knowledge base, a RAG pipeline on Groq LLMs, and RAGAS metrics to evaluate the answers. Shown at 2.5× speed.
Taught live by AI/ML industry practitioners
Proof you can check
Every review on this site comes from a real participant, published with their permission. Attended a VithuPro workshop? Leave a review.
ISO 9001:2015Quality management certifiedMSME RegisteredMinistry of MSME, Govt. of IndiaStartup IndiaDPIIT recognised, Govt. of India
NCS RegisteredNational Career Service, Govt. of IndiaEnroll in two minutes, on WhatsApp
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Questions about this workshop
Is two days enough for all of this?
It is an intensive bootcamp: every module is hands-on, and the pre-workshop Python module means the two days go to AI, not setup. You keep the notebooks to practise afterwards.
Do I need programming experience?
No prior AI background is needed. Basic Python helps; the pre-workshop preparation module covers the Python you need.
Do I need a GPU for fine-tuning and local models?
No. We show you how to run these labs without buying special hardware, and share the setup guide before the workshop.
Can my college or company book this as a custom batch?
Yes. We run it on campus or for teams, and can extend it to 3, 5 or 7 days. Send an enquiry from the Campus & corporate page.
Are the sessions recorded?
Yes. Recordings and materials are shared after each live day, so you can revise or catch up.
What if I miss a session?
Watch the recording and ask your questions in the WhatsApp group. The mentor helps you catch up.
Will I get a certificate?
Yes. Attend the live days to get a verifiable certificate with a unique link, ready for LinkedIn. See how verification works.
What laptop do I need?
A laptop or desktop (not a phone) with at least 4 GB RAM; 8 GB or more is better. A setup guide and a browser-based backup are provided. Setup details.
How do I pay?
After you register, we share the fee and dates on WhatsApp with a secure Razorpay payment link. Full refund up to 4 hours before the start; after that, one free move to the next batch of the same workshop within 3 months. Payment policy.
When are the live sessions?
Batch dates and timings are shared on WhatsApp. Tap "Enroll on WhatsApp" and you get them in the chat right away.
Also open for registration
Each workshop stands on its own. Join any of them directly.
GenAI & Agentic AI Engineering Toolkit
Learn the modern AI toolkit hands-on and build your first working AI agent in Python.
RAG & Agentic AI Applications
Design and build a complete AI application: answers from documents with citations, plus an agentic workflow that takes action.
Enterprise AI Engineering: From Prototype to Production
Make AI systems tested, secure, observable and ready for real users.
The whole GenAI and agentic AI stack, hands-on, in two days.
2 days (intensive) · live online · hands-on