Udemy - AI Agents and Multi-Agent Systems with Agentic AI 100 Labs

  • CategoryOther
  • TypeTutorials
  • LanguageEnglish
  • Total size1.6 GB
  • Uploaded Byfreecoursewb
  • Downloads61
  • Last checkedJul. 03rd '26
  • Date uploadedJul. 02nd '26
  • Seeders 5
  • Leechers16

Infohash : E6CD87C4822106078CBEB2B04E4347E2FCCF9540

AI Agents & Multi-Agent Systems with Agentic AI 100 Labs

https://WebToolTip.com

Published 6/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 7h 48m | Size: 1.62 GB

From prompt-only AI experiments to production-grade autonomous agents, MCP, RAG, LLMOps, and Enterprise AI Platforms

What you'll learn
Architect production-grade Agentic AI systems from first principles.
Build autonomous AI agents capable of reasoning, planning, memory management, and tool usage.
Build sovereign AI infrastructure using open-source models and self-hosted enterprise architectures.
Complete a PhD-level capstone project that nstrates real-world Agentic AI engineering capabilities expected by modern employers.
Engineer multi-agent ecosystems that collaborate, coordinate, review, and self-correct.
Master MCP (Model Context Protocol) to expose and consume enterprise-grade tools securely.
Design and deploy Retrieval-Augmented Generation (RAG) platforms using vector databases and enterprise knowledge systems.
Automate complex business workflows with event-driven and human-in-the-loop architectures.

Requirements
No prior AI experience required.
This course starts from the foundations and progressively builds toward enterprise-scale systems.
Recommended Knowledge
Basic computer literacy
Basic understanding of how software applications work
Familiarity with web browsers and command-line interfaces is helpful but not mandatory

Files:

[ WebToolTip.com ] Udemy - AI Agents and Multi-Agent Systems with Agentic AI 100 Labs
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 1 - Introduction to AI Agents & Multi-Agent Systems with Agentic AI 100 Labs
    • 1 - Introduction.mp4 (128.2 MB)
    10 - MODULE 9 — Security, Governance and Compliance
    • 100 - Lab 90. Enterprise Compliance Architecture.html (14.1 KB)
    • 90 - Security, Governance and Compliance.mp4 (147.0 MB)
    • 91 - Lab 81. AI Threat Modeling.html (13.8 KB)
    • 92 - Lab 82. Identity and Access Management.html (14.9 KB)
    • 93 - Lab 83. Secrets Management.html (14.9 KB)
    • 94 - Lab 84. Secure Tool Invocation.html (13.6 KB)
    • 95 - Lab 85. Agent Sandboxing.html (13.9 KB)
    • 96 - Lab 86. Audit Logging.html (13.9 KB)
    • 97 - Lab 87. Data Privacy Controls.html (14.1 KB)
    • 98 - Lab 88. GDPR-Aware AI Systems.html (15.8 KB)
    • 99 - Lab 89. AI Governance Frameworks.html (15.0 KB)
    11 - MODULE 10 — Reliability, Observability and LLMOps
    • 101 - Reliability, Observability and LLMOps.mp4 (153.0 MB)
    • 102 - Lab 91. Observability Fundamentals.html (14.2 KB)
    • 103 - Lab 92. Agent Telemetry.html (14.0 KB)
    • 104 - Lab 93. Distributed Tracing.html (14.5 KB)
    • 105 - Lab 94. Evaluation Frameworks.html (14.2 KB)
    • 106 - Lab 95. Hallucination Detection.html (13.7 KB)
    • 107 - Lab 96. Reliability Engineering.html (13.8 KB)
    • 108 - Lab 97. LLMOps Pipelines.html (14.2 KB)
    • 109 - Lab 98. Kubernetes Deployment for Agents.html (14.2 KB)
    • 110 - Lab 99. Sovereign AI Platform Deployment.html (14.4 KB)
    • 111 - Lab 100. Sovereign Enterprise Agentic AI Platform Capstone.html (15.6 KB)
    12 - Conclusion
    • 112 - Conclusion.mp4 (133.0 MB)
    2 - MODULE 1 — Foundations and First Success Milestone
    • 10 - Lab 8. Prompt Engineering Fundamentals.html (15.9 KB)
    • 11 - Lab 9. Structured Outputs and JSON Responses.html (14.4 KB)
    • 12 - Lab 10. First Production-Style Agent Milestone.html (15.7 KB)
    • 2 - Foundations and First Success Milestone.mp4 (81.8 MB)
    • 3 - Lab 1. Understanding Agentic AI Architecture.html (14.2 KB)
    • 4 - Lab 2. Local Development Environment Setup.html (14.9 KB)
    • 5 - Lab 3. Python Foundations for AI Agents.html (13.8 KB)
    • 6 - Lab 4. Virtual Environments and Dependency Management.html (15.8 KB)
    • 7 - Lab 5. Git and Collaborative Workflows.html (16.1 KB)
    • 8 - Lab 6. Understanding APIs and Web Services.html (17.6 KB)
    • 9 - Lab 7. Building a Simple Tool-Using Agent.html (14.9 KB)
    3 - MODULE 2 — LLM Engineering Foundations
    • 13 - LLM Engineering Foundations.mp4 (134.4 MB)
    • 14 - Lab 11. LLM Fundamentals.html (13.8 KB)
    • 15 - Lab 12. Tokenization and Context Windows.html (14.7 KB)
    • 16 - Lab 13. Model Selection Strategies.html (14.1 KB)
    • 17 - Lab 14. Open Source vs Hosted Models.html (14.7 KB)
    • 18 - Lab 15. Local Inference with Ollama.html (13.5 KB)
    • 19 - Lab 16. Running Open Models Locally.html (13.7 KB)
    • 20 - Lab 17. Temperature and Sampling Controls.html (14.3 KB)
    • 21 - Lab 18. Prompt Templates.html (13.3 KB)
    • 22 - Lab 19. Response Validation.html (13.5 KB)
    • 23 - Lab 20. Building a Robust LLM Service Layer.html (14.2 KB)
    4 - MODULE 3 — Agent Framework Fundamentals
    • 24 - Agent Framework Fundamentals.mp4 (127.7 MB)
    • 25 - Lab 21. Agent Design Patterns.html (13.8 KB)
    • 26 - Lab 22. Tool Calling Architecture.html (14.5 KB)
    • 27 - Lab 23. Function Calling Workflows.html (15.3 KB)
    • 28 - Lab 24. Agent State Management.html (13.8 KB)
    • 29 - Lab 25. Memory Concepts.html (13.6 KB)
    • 30 - Lab 26. Short-Term Memory Systems.html (12.7 KB)
    • 31 - Lab 27. Long-Term Memory Systems.html (14.8 KB)
    • 32 - Lab 28. Agent Planning Strategies.html (14.9 KB)
    • 33 - Lab 29. Reflection and Self-Correction.html (13.8 KB)
    • 34 - Lab 30. Production Agent Architecture.html (14.8 KB)
    5 - MODULE 4 — MCP Engineering
    • 35 - MCP Engineering.mp4 (143.9 MB)
    • 36 - Lab 31. Introduction to MCP.html (13.0 KB)
    • 37 - Lab 32. MCP Protocol Fundamentals.html (12.9 KB)
    • 38 - Lab 33. MCP Client Architecture.html (15.0 KB)
    • 39 - Lab 34. MCP Server Architecture.html (15.6 KB)
    • 40 - Lab 35. Building Your First MCP Server.html (12.9 KB)
    • 41 - Lab 36. Secure Tool Exposure.html (14.4 KB)
    • 42 - Lab 37. Multi-Tool MCP Integration.html (15.4 KB)
    • 43 - Lab 38. External API Connectivity.html (13.9 KB)
    • 44 - Lab 39. Enterprise MCP Patterns.html (14.8 KB)
    • 45 - Lab 40. Production MCP Platform.html (14.7 KB)
    6 - MODULE 5 — Retrieval-Augmented Generation
    • 46 - Retrieval-Augmented Generation.mp4 (164.8 MB)
    • 47 - Lab 41. RAG Architecture Fundamentals.html (14.9 KB)
    • 48 - Lab 42. Embeddings Explained.html (14.1 KB)
    • 49 - Lab 43. Vector Database Concepts.html (14.3 KB)
    • 50 - Lab 44. Local Vector Storage.html (13.6 KB)
    • 51 - Lab 45. Production Vector Databases.html (14.4 KB)
    • 52 - Lab 46. Document Ingestion Pipelines.html (14.5 KB)
    • 53 - Lab 47. Chunking Strategies.html (14.2 KB)
    • 54 - Lab 48. Metadata Design.html (14.2 KB)
    • 55 - Lab 49. Retrieval Optimization.html (15.4 KB)
    • 56 - Lab 50. Enterprise Knowledge Assistant.html (15.4 KB)
    7 - MODULE 6 — Workflow and Automation Engineering
    • 57 - Workflow and Automation Engineering.mp4 (132.5 MB)
    • 58 - Lab 51. Workflow Automation Fundamentals.html (15.7 KB)
    • 59 - Lab 52. Event-Driven Systems.html (14.7 KB)
    • 60 - Lab 53. Agent-Orchestrated Workflows.html (15.6 KB)
    • 61 - Lab 54. Human-in-the-Loop Design.html (14.6 KB)
    • 62 - Lab 55. Approval Workflows.html (14.8 KB)
    • 63 - Lab 56. Business Process Automation.html (16.2 KB)
    • 64 - Lab 57. Task Queues.html (14.3 KB)
    • 65 - Lab 58. Scheduled Automation.html (15.4 KB)
    • 66 - Lab 59. Long-Running Agent Workflows.html (15.2 KB)
    • 67 - Lab 60. Enterprise Automation Pipeline.html (16.4 KB)

    Code:

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