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Udemy - 2025 Bootcamp Understand and Build Professional AI Agents 2025-1
Course modified date: 4 Mar 2025
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Course content
Sections:
26
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Activities:
0
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Resources:
95
- 1 See what our students say about our bootcamps
- 2 Program Presentation
- 3 Is it recommended to enroll also in our Generative AI Bootcamp
- 4 Alternative Learning Paths and Rhythms Advice to find your best way to learn
- 5 This bootcamp will help you advance professionally
- 6 What will you build in this program
- 7 Opportunities this program will open for your
- 8 Materials included in the program
- 9 Who is this program for
- 10 What makes this program different
- 11 Become part of the Alumni Network
- 12 Distinguish yourself as Honor Student
- 13 Get consulting gigs through the Alumni Network
- 14 Get job offers through the Alumni Network
- 15 Find future startup team members through the Alumni Network
- 16 Introduction to the program director
- 17 Share your progress
- 1 Tips for the students
- 2 Practical tips for the students
- 3 The SECRET to successfully complete this program
- 1 Generative AI and AI Agents
- 1 What are AI Agents and Multi Agents
- 2 AI Agents
- 3 Multi Agents
- 1 The Market of AI Agents
- 1 Key Benefits of AI Agents
- 1 Use Cases of AI Agents
- 1 How to build a Plan to Introduce AI Agents in your Company
- 1 Working with AI Agents Best Practices
- 1 Challenges of AI Agents
- 1 Regulation of AI Agents
- 1 Future of AI Agents
- 1 24 Real Cases of AI Agents to Inspire You
- 2 4 Breakout AI Agents
- 1 What are we going to build
- 1 Introduction
- 2 Learning Stack Videos Detailed Notebooks and stable Code
- 3 Live demo how to download the repo install packages open notebooks run code
- 4 The Path of the Gen AI Engineer
- 1 Introduction to LangGraph
- 2 LangGraph vs LangChain
- 3 Agentic vs Non Agentic LLM Apps
- 4 Degrees of Agentic Behavior
- 5 Why LangGraph And why the word graph in LangGraph
- 6 LangGraph Studio
- 1 Building Basic LangGraph AI Agents
- 2 Facilitating your way through the painful LangGraph documentation
- 3 Apps are often called graphs by the LangGraph team
- 4 Understanding the components of a basic LangGraph app
- 5 LangGraph App that decides to respond with a chatbot or using a tool
- 6 Using a conditional edge as a router between two nodes in LangGraph
- 7 Our first LangGraph Agent the LLM node decides what to do next
- 8 Lets pause and review what we have done so far
- 1 LangGraph AI Agents and Memory
- 2 Adding Short Term Memory to a LangGraph AI Agent
- 3 Formatting the State Schema in LangGraph from TypeDict to Pydantic
- 4 Customizing how the State is updated in LangGraph Agents Reducers
- 5 Multiple State Schemas in LangGraph Agents Use Cases and Implementation
- 6 Lets pause and review what we have done so far
- 1 Memory Efficiency and Memory Persistence in LangGraph AI Agents
- 2 Memory Efficiency in LangGraph Simple Techniques to prevent high token usage
- 3 Memory Summarization in LangGraph to prevent high token usage
- 4 Memory Persistence in LangGraph saving the memory in a SQL database
- 5 Lets pause and review what we have done so far
- 1 Improving LangGraph AI Agents with Human in the loop operations
- 2 Using stream in LangGraph AI Agents
- 3 Using breakpoints and human in the loop to approve the next step of an AI Agent
- 4 Using human in the loop to edit the State of an AI Agent in LangGraph
- 5 AI Agents that can self interrupt using dynamic breakpoints in LangGraph
- 6 Using human in the loop to debug an AI Agent in LangGraph
- 7 Lets pause and review what we have done so far
- 1 Parallelization in LangGraph how to execute multiple nodes at once
- 1 How to Build Multi Agents in LangGraph Using Sub Graphs
- 1 What are Map Reduce Operations and How to build them in LangGraph
- 1 How to build Advanced Multi Agents with LangGraph
- 2 What are we going to build
- 3 Step 1 Plan and Draw the LangGraph Multi Agent
- 4 Step 2 Creating the first subgraph
- 5 Steps 3 and 4 Creating the second subgraph and the parent graph
- 1 AI Agents with Long Term Memory in LangGraph
- 2 Short term vs Long term Memory in LangGraph
- 3 Building an AI Agent with Long term Memory in LangGraph
- 4 Using Complex Memory Schemas in LangGraph for advanced operations
- 5 How to save the Memory of our LangGraph AI Agent in Collections
- 1 How to build a LangGraph AI Agent with Long term Memory
- 2 What are we going to build
- 3 Step 1 Plan and Draw your LangGraph AI Agent
- 4 Step 2 See what TrustCall Extractors are doing behind the scenes with Listeners
- 5 Step 3 Overview of the whole LangGraph AI Agent
- 6 Step 4 Defining the Schemas and the Extractors
- 7 Step 5 Defining the prompts for the LLM Model
- 8 Step 6 Defining the nodes of the LangGraph AI Agent
- 9 Step 7 Defining the Routing Logic of the LangGraph AI Agent
- 10 Step 8 Running the LangGraph AI Agent
- 11 Lets pause and review what we have done so far