Udemy - Agentic AI - Build AI Agents with MCP, FastMCP and Pydantic AI

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Udemy - Agentic AI - Build AI Agents with MCP, FastMCP and Pydantic AI (Size: 787.7 MB)
  Get Bonus Downloads Here.url 204.8 B
  ~Get Your Files Here !
  1. Why Agents From Chatbot to Doer.mp4 25.3 MB
  10. Colab Link To Run The Full Code.url 102.4 B
  10. The Whole Thing Agent to FastAPI to JWT to Production.mp4 412.3 MB
  2. MCP JSON-RPC and Three Method Names.mp4 15 MB
  3. FastMCP The Whole Server in 10 Lines.mp4 14.8 MB
  4. Your First Agent Brain and Hands.mp4 58.4 MB
  5. Multi-Agent Systems An Agent Can Be a Tool.mp4 100.5 MB
  6. LLM Architecture What Is the Brain, Really.mp4 99.6 MB
  7. FP16 How a Number Becomes 16 Bits.mp4 40.1 MB
  8. GGUF Quantization 4GB to 1GB.mp4 16.3 MB
  9. Ollama llama.cpp Wrapped as a Server.mp4 5.5 MB
  Bonus Resources.txt 102.4 B

Description


Agentic AI: Build AI Agents with MCP, FastMCP & Pydantic AI
https://WebToolTip.com
Published 7/2026

Created by Nandakishor M

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch

Level: All Levels | Genre: eLearning | Language: English | Duration: 10 Lectures ( 1h 23m ) | Size: 787.7 MB
Learn JSON-RPC and the Model Context Protocol, build multi-agent systems, run local LLMs, and ship a JWT-secured agent
What you'll learn

⚡ Build AI agents from first principles using the Model Context Protocol (MCP), understanding the JSON-RPC loop behind every agent.

⚡ Turn any Python function into an agent tool in minutes with FastMCP, and orchestrate multi-agent, multi-tool systems using Pydantic AI.

⚡ Run large language models locally with Ollama and GGUF quantization, so your agents work offline with no API bills.

⚡ Deploy a working AI agent as a production REST API secured with JWT authentication using FastAPI.

⚡ Understand LLM internals that matter for agents: tokens, embeddings, attention, FP16 and quantization.
Requirements

❗ Comfortable writing basic Python (functions, classes, pip). No AI or machine learning background needed, everything about agents and LLMs is taught from scratch.

❗ A computer that can run Python 3. A GPU is helpful for local models but not required.

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