Complete Agentic AI Bootcamp With LangGraph and Langchain

183 lectures45h 42m totalSubtitles & transcript search26 sections

Full lifetime access · picks up where you left off

Curriculum

26 sections · 183 lectures

01Introduction To the Course1 · 2m
02Installation Of Anaconda And VS Code IDE3 · 28m
  • Installation Of Anaconda And VS Code Editor11:35
  • Creating Virtual Environments Using Conda5:59
  • Creating Virtual Environments Using UV Package Manager10:49
03Python Prerequisites40 · 11h 41m
  • Getting Started With VS Code10:37
  • Python Basics- Syntax And Semantics20:18
  • Variables In Python18:55
  • Basic Datatypes In Python9:53
  • Operators In Python16:17
  • Conditional Statements(if,elif,else)21:03
  • Loops In Python28:03
  • List And List Comprehension In Python37:08
  • Practical Exmaples Of List9:51
  • Sets In Python21:05
  • Dictionaries In Python38:19
  • Tuples In Python22:35
  • Getting Started With Functions24:22
  • More Coding Examples With Functions28:03
  • Python Lambda Funbction9:45
  • Maps Functions Python11:09
  • Filter Function In Python9:01
  • Import Modules And Package In Python17:07
  • Standard Library Overview17:44
  • File Operation In Python17:08
  • Working With File Paths8:44
  • Exception Handling25:00
  • Classes And Objects In Python22:56
  • Inheritance In OOPS19:01
  • Polymorphism In OOPS19:09
  • Encapsulations In OOPS22:12
  • Abstraction In OOPS9:09
  • Magic Methods In Python8:04
  • Operative Overloading In Python8:32
  • Custom Exception Handling7:06
  • Iterators In Python6:26
  • Generators In Python11:07
  • Fucntion Copy.Closures and Decorators21:15
  • Numpy In Python28:17
  • Pandas-DataFrame And Series29:10
  • Data Manipulation With Pandas And Numpy24:39
  • Reading Data From Various Data Source Using Pandas15:05
  • Logging Practical Implementation In Python14:38
  • Logging With Multiple Loggers4:40
  • Logging With A Real World Examples7:44
04Getting Started With Pydantic In Python2 · 36m
  • Introduction To Pydantic14:08
  • Pydantic Practical Implementation21:43
05Langchain Hands On13 · 2h 40m
  • Getting Started With Langchain And Open AI12:02
  • Creating Virtual Environment7:12
  • Important Components Of LangChain13:10
  • Data Ingestion With Documents Loaders22:44
  • Recursive Character Text Splitter12:57
  • Character Text Splitter With Langchain3:53
  • HTML Header Text Splitter7:01
  • Recursive Json Text Splitter6:49
  • Introduction To OPENAI Embeddings22:21
  • Ollama Embeddings15:44
  • HuggingFace Embeddings10:21
  • Vector Stores-FAISS16:34
  • Vector Store And Retriever- Chroma DB9:33
06Getting Started With OpenAI And Ollama6 · 1h 24m
  • Building Important Components Of Langchain21:46
  • Building GENAI Apps17:38
  • Understanding Retrievers And Chains21:00
  • Introduction To Ollama And Set Up7:24
  • Simple GenAI App Using Ollama12:57
  • Tracking GENAI App Using Langsmith2:53
07Building Basic LLM Application Using LCEL3 · 49m
  • Getting Started With Open Source Models Uing Groq API16:29
  • Building LLM Prompt And StrOutput Parser Chain With LCEL14:36
  • Deploy Langserve Runnable And Chains As API17:38
08Building AI agents With Conversation History Using Langchain4 · 1h 16m
  • Building Chatbot With Message History Using Langchain23:12
  • Working With Prompt Template And Message ChatHistory Using LAngchain13:48
  • Managing the Chat Conversation History Using Langchain12:26
  • Working With VectorStore And Retriever26:32
09AI Agents Vs Agentic AI2 · 30m
  • What is Ai Agent Vs Agentic AI18:25
  • Some More Examples11:44
10Updated Langchain Version V112 · 2h 31m
  • Langchain Updates V13:52
  • Creating Virtual Environment Using UV Package11:59
  • Creating Agents Using Langchain18:28
  • Langchain LLM Model Integration12:11
  • Invoke And Batch Streaming Using Langchain7:33
  • Tools In Langchain9:13
  • Messages Types In Langchain16:08
  • LLM structured Output Using Pydantic16:28
  • LLM structured Output Using TypeDict6:10
  • LLM structured Output Using DataClass6:38
  • Middleware Summarization27:40
  • Human In The Loop MiddleWare14:53
11Getting Started With LangGraph8 · 1h 56m
  • Introduction To LangGraph19:44
  • Getting Started LangGraph Application- Creating The Environment11:45
  • Setting Up OpenAI API Key7:03
  • Setting Up GROQ API KEY5:46
  • Setting Up LangSmith API Key6:24
  • Developing A Simple Graph or Workflow Using LangGraph- Building Nodes And Edges21:50
  • Building Simple Graph StateGraph And Graph Compiling11:27
  • Developing LLM Powered Simple Chatbot Using LangGraph31:44
12LangGraph Components13 · 3h 19m
  • State Schema With DataClasses23:35
  • Pydantic9:06
  • Chain In LangGraph19:59
  • Routers In LangGraph9:19
  • Tools And ToolNode With Chain Integration- Part 128:48
  • Tools And Tool Node With Chain Integration-Part 28:02
  • Building Chatbot With Multiple Tools Integration- Part 123:39
  • Building Chatbot With Multiple Tools Integration-Part 29:02
  • Introduction To Agents And ReAct Agent Architecture In LangGraph15:03
  • ReAct Agent Architecture Implementation12:53
  • Agent With Memory In LangGraph17:54
  • Streaming In LangGraph16:44
  • Streaming using astream events Using Langgraph5:05
13Debugging LangGraph Application With LangSmith1 · 21m
  • LangGraph Studio20:40
14Different Workflows In LangGraph7 · 1h 28m
  • Prompt Chaining5:29
  • Prompt Chaining Implementation With Langgraph15:51
  • Parallelization8:48
  • Routing22:13
  • Orchestrator-Worker6:36
  • Orchestrator Worker Implementation16:48
  • Evaluator-optimizer12:01
15Human In The Loop In LangGraph4 · 52m
  • Human In The Loop With LangGraph Workflows21:50
  • Human In the Loop Continuation12:26
  • Editing Human Feedback In Workflow6:52
  • Runtime Human Feedback In Workflow10:23
16RAG With LangGraph7 · 1h 43m
  • Agentic RAG Theoretical Understanding13:02
  • Agentic RAG Implementation- Part 122:42
  • Agentic RAG Implementation-Part 217:19
  • Corrective RAG Theoretical Understanding7:14
  • Corrective RAG Practical Implementation13:55
  • Adaptive RAG Theoretical Understanding11:55
  • Adaptive RAG Implementation17:02
17Vectorless RAG2 · 51m
  • Vectorless RAG With PAgeIndex Tutorials29:18
  • Traditional Vs Vectorless RAG21:43
18Guardrails1 · 38m
  • Guardrails With Langchain38:14
19LLM Gateways1 · 43m
  • LLM Gateways Understanding And Implementation42:56
20End To End Agentic AI Projects With LangGraph10 · 1h 51m
  • Introduction And Overview3:56
  • Project Set Up With VS Code7:14
  • Setting up The Github Repository7:44
  • Setting Up The Project Structure14:23
  • Designing The Front End Using streamlit27:01
  • Implementing The LLM Module In Graph Builder9:15
  • Implementing The Graph Builder Module13:11
  • Implementing The Node Implementation6:33
  • Integrating the Entire Pipeline With Front End13:25
  • Testing The End To End Agentic Application8:25
21End To End Agentic Chatbot With Web Search Functionality4 · 42m
  • Introduction To The Project5:38
  • Implementing The Front End With Streamlit7:04
  • Implementing GraphBuilder and Search Tools Pipeline13:45
  • Implementing Node Functionality With End To End Agentic Pipeline15:15
22AI News Summarizer End To End Agentic AI Projects7 · 50m
  • Project Introduction8:11
  • Building the Front End With Streamlit7:33
  • Building The AI News State Graph Builder6:15
  • Tavily Client Search Fetch News Node Implementation7:11
  • AI News Summarize Node Functionality Implementation3:08
  • Save Results Node Functionality Implementation7:11
  • Running The Entire AINEWS Agentic Workflow10:47
23End To End Blog Generation Agentic AI App10 · 1h 48m
  • Introduction And Project Demo7:41
  • Building Project Structure Using UV Package7:04
  • Blog Generation Grpah Builder And State Implementation15:59
  • Blog Generation Node Implementation Definition12:23
  • Creating Blog Generating API Using FAST API17:30
  • Integrating Langgraph Studion For Debugging14:16
  • Blog Generation And Translation With Language2:45
  • Building Blog Generation And Translation Graph Builder10:18
  • Blog Generation And Translation Node Implementation15:56
  • Testing In Postman And Langgraph Studio3:39
24Model Context Protocol7 · 1h 51m
  • Introduction To Model Context Protocol17:26
  • Important Components Of MCP7:08
  • Communication Between Components Of MCP8:34
  • Demo Of MCP With Claude Desktop20:02
  • Cursor IDE Installation6:26
  • Getting Started With Smithery AI16:16
  • Building MCP Servers With Tools And Client From Scratch Using Langchain34:45
25Claude Code7 · 2h 11m
  • Introduction To Claude Ecosystem20:11
  • Claude Code Worrking And Setup32:53
  • Claude Code Agents18:03
  • Agent Views In Claude Code9:51
  • Agent Teams With Claude Code14:26
  • Hooks In Claude Code14:26
  • Skills And Plugins In Claude Code21:14
26Building Deep Agents With Langchain8 · 2h 42m
  • Introduction To Deep Agents And Basics Implementation44:12
  • Deep Agents Customization1:45
  • Introduction To Backends In Deep Agents19:34
  • Deep Agents Vs Claude SDK13:34
  • Introduction To Context Engineering And Its Types34:12
  • Using Skills For Context Engineering24:30
  • Sub Agents In Deep Agents16:42
  • Implementating Project With All Features7:48