Generative AI And Agentic AI Workshop
Ideal for Students and Professionals who want to Build and Deploy GenAI
From Zero to Hero in less than 24 hrs
Only for € 500 € 250
July 11, 2026 9:00 am
July 26, 2026 5:00 pm
Mode
Online on Zoom
Language
English
Limited Seats - Hurry Up
Is This Bootcamp For You?
This bootcamp is designed for people who are tired of just chatting with AI and want to start building with it:
Data scientists and Python programmers
Who are moving into LLMs, RAG, and multi-agent systems
Enterprise automation teams
Who are working on document processing, workflow automation, and tool-based AI assistants.
Project Managers
who want to learn GenAI
AI/ML developers
who want to build agentic applications with Python frameworks.
What You'll Be Able to Do After Three Hours
By the end of this bootcamp, you won’t just “understand” AI — you’ll have built with it.
Understand LLM architecture
Understand how Agents , models, embeddings, and Vector DBs actually work together to power modern AI apps.
Build LangChain applications
Learn how to use powerful frameworks like Langchain for Building Multiagent Solutions.
Create a RAG demo from your own data
Build an RAG pipeline that can answer questions from your PDFs / documents.
Unlock agentic AI workflows
Use frameworks like LangChain, CrewAI Orchestrate multi-step, tool-using agents.
Walk away with a finished project
You’ll have a working AI project that you can improve, show to clients, or use as a portfolio piece.
Only for € 500 € 250
Bootcamp Schedule (20 Hours, Live + Hands on Sessions)
Module 1 - Foundations of Python for Agentic AI
- Virtual Environment pip
- uv
- Packages
- API calls
- JSON
- Classes Decorators
- Type hints
Module 2 - Agentic AI with Python Frameworks
- Agent frameworks (LangChain, AutoGen, CrewAI – overview)
- Practical: Building an AI Research Assistant Agent
- LLM Prompting & LangChain Basics
- Vector Databases & RAG (Retrieval-Augmented Generation)
- Autonomous Agents (Agentic AI)
Module 3 - Multi-Agent Systems & Tools
- Multi-agent coordination
- Role-based agents
- Tool calling
- API & document access
How This Bootcamp Is Different
End-to-end agentic AI journey
Covers the full stack from Python foundations and LLM prompting to RAG, multi-agent systems, evaluation, and deployment, so participants can go from concept to production-ready agents in one program
Hands-on with leading frameworks and tools
Learners work directly with agent frameworks (LangChain, AutoGen, CrewAI), vector databases, LangSmith, Streamlit, Gradio, FastAPI, and Azure, mirroring modern enterprise AI stacks
Enterprise-focused, production-oriented design
The curriculum emphasizes observability, hallucination checks, monitoring, and deployment best practices, making it suitable for BFSI and other regulated domains that need robust, auditable AI systems.
Real-world Scenarios
Examples you can adapt to your job, freelancing, or startup.
Clear Roadmap
You leave with a next-step learning & project plan, not confusion.
What You Will Walk Away With
Deliverables
Multi-Agent Workflow for a Real Task
Production-ready LLM Web App
Evaluation & Monitoring Dashboard
Case study toolkit & reference materials
Certificate of Completion
You’ll also get a checklist of all tools & commands used during the session so you can redo everything on your own later.
FAQs.
A basic level of technical comfort helps (running commands, editing config files, etc.), but you don’t need to be a senior developer. If you’ve ever followed a tech tutorial before, you’ll be okay.
We’ll primarily work with:
Ollama & Docker (for running local LLMs)
DeepSeek-R1 (as a model example)
A VectorDB setup (for embeddings & retrieval)
Agno, CrewAI & MCP (for agent workflows)
You’ll receive a tool checklist before the session so you can install things in advance.
A modern laptop with at least 16GB RAM is recommended. For heavier models, we’ll also show options to run smaller models or use cloud setups.
Yes, the session will be recorded and made available for 45 days after the bootcamp.
You’ll get the code snippets / commands / structure so you can rebuild the project at your own pace.
Tickets are non-refundable, but you can transfer your seat to another person.
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