Building Agentic AI Systems
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Index

Schedule

Day Description Materials Assignment
1 Overview
Introduction: LangChain, LangGraph, LangSmith.
[Lesson]
[Case Studies]
[Assignment 1]
Agents
Models, Messages, Prompts, Structured Output, Tools, and Internet Search.
[Notebook] [Assignment 2]
Sub Agents
Build a personal assistant with agents as tools.
[Notebook] [Assignment 3]
2 RAG Overview
Building a knowledge base. Retrieval pipeline and building blocks. RAG Architectures.
[Lesson]
Embeddings
What are embeddings and how do they compare similarity?
[Notebook]
Semantic Search
Indexing and retrival of documents based on meaning.
[Notebook] [Assignment 4]
RAG Chain and RAG Agent
Answer questions based on specific sources of information.
[Notebook] [Assignment 5]
3 Context and State
Short-term, long-term memory and context.
[Notebook]
Customer Support Agent
Apply the State Machine pattern to resolve customer issues and escalate to humans when necessary.
[Notebook]
4 Thinking in LangGraph
[Lesson]
Workflow Patterns
[Notebook]
LangSmith
[Lesson]

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Pre-requisites

  • Python Basics. To prepare or refresh: المقدمة البايثونية للبرمجة باللغة العربية