- Artificial Intelligence and Machine Learning
- Key types of Machine Learning- Supervised & Unsupervised Learning
- Basics of Deep Neural Network
- Natural Language Processing & Generative AI
- Overview of LLMs & Multimodal LLMs
Lab: Multimodal Embeddings
Lab: Subword tokenization
Demo - Solving ML, NLP Problems using LLMs
- Concept of Retrieval Augmented Generation (RAG) with 2 real-life examples
- Data pipeline for RAG
- Demo/ Code walkthrough- Naïve RAG
- Breakout Room Activity- Understanding code/ flow of an E2E RAG pipeline
- Business use cases of RAG Apps across Industries and Horizontals/ Functions, including Vertical AI Agents
- Chunking Strategies
- Creating Vector embeddings and storing them in a Vector database, with examples
- Retrieval Mechanics & Similarity/ Vector search techniques
- Langchain for RAG Development
- Techniques for improving RAG accuracy- Reranking, chunk optimization, others
- Langflow for low-code, no-code visual modeling-based RAG development
Lab: Building RAG Data ingestion, indexing, retrieval, and generation pipeline
Lab: FileSearch Tool for Managed RAG- Google Gemini
Lab: Data ingestion & indexing - Multiple files
- Overview of AI Agents/ Agentic AI & role of LLMs/ SLMs
- Design patterns of AI Agentic workflows- Reflection, Tool use/ function calling, Planning, Multi-agent collaboration
- Business use cases of AI Agents across Industries and Horizontals/ Functions, including Vertical AI Agents
- Technical use cases of AI Agents (in SDLC automation)
- Step-by-step - Designing an AI Agent
- Advanced Context Engineering for Agents
- Agentic Memory - Long-term, short-term, with demos
Lab: Agentic Memory
- Agents controlling the browser, keystrokes, and mouse clicks/ computer control
- Deep Agents- working with complex, long-running tasks
- Building a browser-based agent for Software Testing
- AI Agent/ Agentic AI Pricing models & how they are disruptive to existing SAAS models
- Breakout Room Activity: Building use case and specs for an AI Agent
Demo- AI Agent for Web UI Testing
- Tool use/ function calling with API integrations
Demo - Tool use/ function calling
- Model Context protocol (MCP)
- Connecting Agents with 3rd party apps using MCP Servers
- MCP Host and MCP Client
Demo- Setting up MCP Servers on Cline and GitHub Copilot in VSCode
Demos- Working with MCP Servers from Zapier, Composio, AWS/ Azure/ GCP
- MCP Server Security
- Getting website data using MCP-B and llms.txt
- Real-time web data access with tools like Tavily, Serper, and FireCrawl
Demo- Building your own MCP Server and hosting on the Cloud
Lab: Use GitHub Copilot Agent mode & connect with GitHub MCP Server & Playwright MCP Server for specific tasks
Lab: Build an AI Agent with MCP Server Integration
- TOON - Token object-oriented notation
Lab: Working with TOON

UK