Udemy - Agentic AI - Deliver a successful chatbot PoC with LangGraph

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Udemy - Agentic AI - Deliver a successful chatbot PoC with LangGraph (Size: 417.1 MB)
  1 - Assistants.html 9.1 KB
  1 - Knowledge Base - electricity plan data.html 3.2 KB
  1 - Knowledge Base - spending data.html 3.4 KB
  1 - LangGraph graph.html 19.8 KB
  1 - Prompts.html 6.9 KB
  1 - Section intro - what we are coding.html 2.4 KB
  1 - Setup.html 1.3 KB
  1 - State.html 2.7 KB
  1 - Tools.html 9.8 KB
  1 -Demo day and what to expect.mp4 11.1 MB
  1 -Key takeaways.mp4 11.4 MB
  1 -Motivation and scope.mp4 27.7 MB
  1 -Running our customer support bot.mp4 92.3 MB
  1 -Section intro.mp4 7.8 MB
  2 -Course content overview.mp4 7.9 MB
  2 -Expected interactions.mp4 7.9 MB
  2 -Fine-tuning prompts.mp4 27.6 MB
  2 -Guardrails.mp4 32.1 MB
  3 -Enabling technologies.mp4 8.7 MB
  3 -Fine-tuning tools.mp4 9.4 MB
  3 -Functional specifications.mp4 17.7 MB
  3 -Performance optimization points.mp4 48.6 MB
  4 -Customer support use case.mp4 11.8 MB
  4 -Fine-tuning graph structure.mp4 12.8 MB
  4 -Performance profiling (sizing).mp4 24.2 MB
  4 -Technical specifications.mp4 6.4 MB
  5 -Conceptual architecture.mp4 12.5 MB
  5 -LLM infrastructure (ollama).mp4 17.3 MB
  6 -Handling long context.mp4 17.1 MB
  Bonus Resources.txt 102.4 B
  Get Bonus Downloads Here.url 204.8 B
  ▲ 33 total files

Description


Agentic AI: Deliver a successful chatbot PoC with LangGraph

https://WebToolTip.com

Published 2/2025
Created by Peniac Courses
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Expert | Genre: eLearning | Language: English | Duration: 31 Lectures ( 1h 33m ) | Size: 417 MB

Practical insights on using LLMs, agentic AI, and LangGraph for a successful GenAI-powered chatbot Proof-of-Concept

What you'll learn
Effectively plan and manage a chatbot PoC project
Map functional and technical requirements to a LangGraph architecture
Develop a functional LLM-powered chatbot PoC
Prepare for production by addressing key engineering and performance factors

Requirements
Good Python programming skills
Basic understanding of large language models
Basic understanding of retrieval-augmented generation
Familiarity with graphs
Basic familiarity with LangGraph

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