• This course is designed for non-coding software engineers, business analysts, QA, product managers who want to build Generative AI based applications without writing any code – no machine learning experience required.

• No programming experience required, experience playing with ChatGPT or equivalent LLMs will be nice but not required

Course Outline:

1. Introduction to Large Language Models (LLMs)
   1. A brief history of Generative AI and LLMs
   2. What is a Large Language Model?
   3. Why LLMs are disrupting industries
   4. Hands-on: Create the lab environment and work with LLM
2. Using Model Prompts and Prompt Templates
   1. What is a prompt?
   2. Types of prompts: zero-shot, one-shot, few-shot
   3. Hands-on: Build a simple chat application using prompt and prompt templates
3. Build a captivating conversation using different types of documents formats
   1. Introduction to data connectors
   2. Uploading and interacting with CSV, PDF, and other formats
   3. Hands-on: Load a CSV file and get insights in the data
4. Using Agents to perform tasks
   1. What are agents in context of AI?
   2. Types of agents: tool-using agents, reasoning agents, reactive agents
   3. Hands-on: couple of labs using agents
5. Building RAG applications
   1. What is Retrieval Augmented Generation (RAG)?
   2. Why RAG is important for custom knowledge applications
   3. Understanding embeddings and vector stores
   4. Hands-on: Build an RAG application with vector storage and embeddings
6. Using Agentic-AI to build multi-agent applications
   1. What is Agentic-AI?
   2. How agents can collaborate to perform complex workflows
   3. Tools that make multi-agent applications possible in no-code platforms
   4. Hands-on: Build financial report application using multiple agents

Training material provided: Yes (Digital format)

Hands-on Lab: Students can use either open-source models or OpenAI models. Instructions will be provided to install tools for local machines or a website build use (free of charge) to build applications