Become an AI (LLM + RAG) Developer in 2 Months
A live, project based training by Cydenium. You build real AI (LLM + RAG) applications from scratch. Learn how LLMs like GPT and LLaMA actually work internally, and understand Retrieval Augmented Generation in depth. By the end of this bootcamp, you'll be able to build your own AI applications.
Companies aren't hiring people to train AI models. They're hiring people who can connect an LLM to their own data.
Generative AI is moving into internal knowledge systems, customer support, document search and research assistants across software, healthcare, finance, education and legal services. Most teams don't need someone who can train a foundation model from scratch. They need someone who can integrate an existing LLM with business data using RAG and modern AI frameworks. That is exactly what this program teaches, step by step.
Python
NLP
Embeddings
LLM Integration
Memory Chatbots
Manual RAG
Automated RAG
Streamlit UI
Deployment
AI apps you'll actually ship
Every module ends in working code. By the end of the bootcamp you'll have built six kinds of assistants that mirror real products companies are adopting right now.
Company Assistant
Answers employee questions on leave policy, HR documents and internal knowledge, so nobody has to dig through PDFs.
PDF Chatbot
Upload any PDF and chat with it directly. Summaries, source citations and follow up questions included.
Medical AI Assistant
Retrieves and explains answers from medical reference documents, with sources attached to every response.
Research Copilot
Summarizes long research material and surfaces the key points and citations in seconds.
Multi-Doc RAG Bot
Combines multiple documents into one searchable knowledge base and answers questions across all of them at once.
Custom AI Chatbot
Your own branded chatbot with real memory, built, deployed and ready to demo by the end of the program.
10 modules, about 60 hours, no filler
Every topic is taught through live coding, guided exercises and a mini practical before moving on. Tap a module to see what's inside.
Build the Python foundation required for AI development. Python is the primary language used for AI, LangChain and RAG work.
Topics
You'll be able to
- Write clean Python programs
- Work confidently with data structures
- Build command line applications
Understand how text is processed before it ever reaches an LLM. This module lays the conceptual groundwork for embeddings and retrieval.
Topics
You'll be able to
- Process raw text reliably
- Understand the full NLP pipeline
- Prepare text for AI applications
Learn how computers turn language into vectors. Embeddings are the backbone of semantic search and every vector database you'll use later.
Topics
You'll be able to
- Explain vector representations clearly
- Understand semantic similarity
- Be fully ready for RAG
Understand how modern LLMs evolved, without the heavy math. Good for interviews and for making sense of the systems you're building on.
Topics
You'll be able to
- Explain how LLMs generate text
- Understand why transformers replaced RNNs
Build chatbots that remember earlier turns in a conversation. Memory is widely used in enterprise AI assistants.
Topics
You'll be able to
- Develop context aware chatbots
- Choose the right memory strategy for a use case
Connect your applications with modern LLM providers using LangChain, one of the most widely used frameworks for AI development.
Topics
You'll be able to
- Integrate LLM APIs end to end
- Design structured, reliable prompts
- Build full chatbot workflows
Build a Retrieval Augmented Generation pipeline from scratch, with nothing hidden behind a library.
Topics
You'll be able to
- Understand every RAG component from first principles
- Build a retrieval pipeline manually
Use LangChain's built in abstractions to turn your manual pipeline into a production style RAG system with far less boilerplate.
Topics
You'll be able to
- Develop scalable, production style RAG systems
- Cut boilerplate using LangChain abstractions
Turn your AI code into something people can actually click through. Streamlit is one of the fastest ways to prototype an AI product.
Topics
You'll be able to
- Build interactive AI applications with a real UI
- Deploy demo ready projects
Bring every concept together into complete AI solutions and leave with production style projects ready to show in interviews.
Topics
You'll be able to
- Deliver complete, end to end AI applications
- Walk into interviews with a real portfolio
8 projects, one for every stage of the journey
You move step by step from a basic console chatbot to enterprise grade RAG systems. Each one is a project you can show, not just describe.
Console AI Chatbot
A command line chatbot connected directly to an LLM, the foundation for every project that follows.
AI Chatbot with Memory
A chatbot that remembers earlier turns in the conversation using multiple memory strategies.
Manual RAG Chatbot
Every RAG component built by hand: PDF loading, chunking, embeddings, FAISS and retrieval.
Automated PDF RAG Assistant
A production style PDF chatbot built using LangChain's retrieval abstractions.
Company Employee Assistant
An internal assistant that answers company policy and documentation questions.
Multi-PDF Knowledge Assistant
Upload multiple documents and ask questions across all of them at once.
AI Research Copilot
Summarize documents, extract insights and answer research questions on demand.
Medical Knowledge Assistant
Answer questions from medical reference documents, with citations attached.
Tools and technologies you'll actually use
Roles this prepares you for
Employers value candidates who can show working applications and explain the architecture behind them, not just describe concepts. That's what this bootcamp is built to produce.
Industries adopting LLM + RAG
What you get, beyond the curriculum
- ✓ Hands-on live projects, not recorded theory
- ✓ Skills mapped to what companies actually use today
- ✓ Beginner friendly, no prior AI experience needed
- ✓ Certificate of completion
- ✓ Lifetime access to session materials
- ✓ Doubt support and a peer community
- ✓ Resume and portfolio guidance
- ✓ Career support after the bootcamp ends
Who this bootcamp is built for
B.Tech / B.E., BCA, MCA
Starting their first AI role
Python developers moving into AI
Upskilling while working
Before you register
Quick answers about experience, live classes, projects and the free demo.
No. The bootcamp starts from Python basics in Module 1 and builds up step by step. Anyone comfortable learning something new can follow along.
It's fully live. Every session includes concept explanation, live coding and doubt solving, so you write the code yourself instead of copying a finished project.
Eight working AI projects you can show in an interview, a certificate of completion and a working understanding of Python, NLP, embeddings, LangChain and RAG.
A 2 hour live session where you see the kind of projects you'll build, ask questions directly and get a clear walkthrough of the full curriculum before deciding to join.
Your 2 months to becoming an AI developer starts with a free demo class.
Live projects, real Q&A, and a walkthrough of exactly what you'll build. No prior AI experience required.