Udemy - Agentic AI From Zero to Expert - 100 Real Labs
About Udemy - Agentic AI From Zero to Expert - 100 Real Labs
Overview
Agentic AI From Zero to Expert: 100 Real Labs https://WebToolTip.com Published 6/2026 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 7h 51m | Size: 1.72 GB From simple AI prompts to production autonomous agents using LangGraph, RAG, MCP, Kubernetes, and AI Ops. What you'll learn Build multi-agent platforms that collaborate, review, validate, and coordinate work. Architect production-grade autonomous AI agents using modern agent engineering principles. Bui
Frequently Asked Questions
How do I download Udemy - Agentic AI From Zero to Expert - 100 Real Labs?
Click the magnet or torrent download button on this page to start downloading Udemy - Agentic AI From Zero to Expert - 100 Real Labs. A BitTorrent client is required.
What is the file size of Udemy - Agentic AI From Zero to Expert - 100 Real Labs?
The total size of Udemy - Agentic AI From Zero to Expert - 100 Real Labs is 1.7 GB.
How many seeders are available for Udemy - Agentic AI From Zero to Expert - 100 Real Labs?
Udemy - Agentic AI From Zero to Expert - 100 Real Labs currently has 21696 seeders, which affects download speed.
What category is Udemy - Agentic AI From Zero to Expert - 100 Real Labs in?
Udemy - Agentic AI From Zero to Expert - 100 Real Labs is listed under Other on 1337x.
Agentic AI From Zero to Expert: 100 Real Labs
https://WebToolTip.com
Published 6/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 7h 51m | Size: 1.72 GB
From simple AI prompts to production autonomous agents using LangGraph, RAG, MCP, Kubernetes, and AI Ops.
What you'll learn
Build multi-agent platforms that collaborate, review, validate, and coordinate work.
Architect production-grade autonomous AI agents using modern agent engineering principles.
Build reasoning, planning, memory, and tool-using agents from scratch.
Master LangGraph workflows for stateful and reliable agent execution.
Design enterprise RAG systems using embeddings, vector databases, and hybrid retrieval.
Develop MCP-based tool ecosystems that safely connect agents to real systems.
Implement security, governance, audit logging, and compliance controls for AI systems.
Deploy scalable AI workloads using Docker, Kubernetes, Terraform, and GitOps.
Monitor, evaluate, and troubleshoot agents using OpenTelemetry, Prometheus, and Grafana.
Construct a sovereign enterprise AI platform in the PhD-level Lab 100 capstone.
Requirements
Recommended Requirements
1. Basic computer literacy.
2. No previous AI experience required.
3. Basic Python knowledge is helpful but not mandatory.
4. Familiarity with command-line basics can accelerate learning.
Recommended Hardware
1. 16 GB RAM
2. Quad-core CPU
3. 100 GB free storage