About
Class 1 & Class 2: Same as Basic Course
Class 3: Advanced Prompting Strategies
Theory (1 hour):
Advanced prompting techniques: Chain of Thought (CoT), Self-Consistency, Tree of Thoughts
How to decompose and chain prompts for more complex tasks
Understanding embedding-based models
Practice (1 hour):
Google Colab: Build a prompt chain using an AI assistant to solve a multi-step task text-based question-answering using LangChain.
Class 4: Introduction to Retrieval-Augmented Generation (RAG)
Theory (1 hour):
What is Retrieval-Augmented Generation (RAG)
Embeddings, vector databases, and dense retrieval methods
Combining retrieval with LLM for improved accuracy
Practice (1 hour):
Google Colab: Create a RAG system using LangChain, demonstrate how to retrieve documents, and generate responses based on the retrieved data.
Consulting advice:
We offer personalized consulting for your generative AI projects. Whether you're starting out or looking to automate workflows with tools like LangChain or LangGraph, we’ll help identify the best strategies and solutions. This includes streamlining processes, optimizing AI automation, and ensuring scalability. You'll gain practical insights to apply AI effectively and ensure project success.