Tutorials > AI Agents & Multi-Agent Systems with Agentic AI 100 Labs
AI Agents & Multi-Agent Systems with Agentic AI 100 LabsDate: 26 August 2026 | Posted by: AD-TEAM |
![]() AI Agents & Multi-Agent Systems with Agentic AI 100 Labs MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English (US) | Duration: 8 h | Size: 1.62 GB This course contains the use of artificial intelligence. I only charge a fee solely for the time invested in building this comprehensive curriculum. Stop Building Demos. Start Engineering Systems. The AI industry is experiencing a dangerous trend. Thousands of developers are learning "Vibe Coding." They can prompt a model. They can build a chatbot. They can connect an API. But when asked to design a reliable, observable, secure, scalable Agentic AI platform that operates inside a real organization, most projects collapse. Why? Because production AI is not prompt engineering. Production AI is engineering. It requires architecture, orchestration, memory systems, tool integrations, governance, observability, deployment pipelines, security controls, and operational reliability. This course was built to close that gap. The Complete 100-Lab Journey This is not a theory course. This is not a collection of disconnected demos. This is a carefully designed, progressive engineering curriculum containing 100 hands-on labs that move you from absolute beginner to advanced Agentic AI Architect. You will begin by learning: AI agent fundamentals Python foundations APIs Prompt engineering Tool usage Structured outputs Then you'll progress into: LLM engineering Model selection Local inference Open-source AI deployment Service-layer architecture Next, you'll master: Agent frameworks Memory systems Planning architectures Reflection loops Self-correcting agents And then the real engineering begins. What's Inside? Module 1 — Foundations Build your first production-style AI agent and understand how modern Agentic AI systems actually work. Module 2 — LLM Engineering Learn how language models function, how inference works, and how professionals design robust AI service layers. Module 3 — Agent Engineering Design agents that think, plan, remember, and execute tasks using proven architectural patterns. Module 4 — MCP Engineering Master the protocol rapidly becoming the industry standard for connecting AI systems to tools and enterprise resources. Module 5 — Enterprise RAG Build knowledge assistants capable of searching, retrieving, and reasoning over large-scale organizational knowledge. Module 6 — Workflow Automation Transform AI from a conversation engine into an operational platform that drives business processes. Module 7 — Multi-Agent Systems Create teams of specialized agents that collaborate, review, validate, and execute complex objectives. Module 8 — Data Engineering Learn how enterprise AI systems process, validate, govern, and analyze information. Module 9 — Security & Governance Implement identity management, secrets handling, compliance controls, audit logging, and responsible AI practices. Module 10 — Reliability & LLMOps Deploy and operate AI systems using observability, evaluation frameworks, CI/CD pipelines, Kubernetes, and production operations. The Life-Changing Final Project Lab 100: Sovereign Enterprise Agentic AI Platform Most courses end with a chatbot. This course ends with an enterprise platform. You will design and deploy a complete Agentic AI ecosystem featuring: Autonomous research agents Planning agents Compliance agents Reporting agents Enterprise RAG MCP integrations Long-term memory Kubernetes deployment Observability dashboards Governance controls Human approval workflows Security architecture Disaster recovery procedures This is the type of project normally found inside enterprise consulting engagements, advanced research programs, and high-end engineering teams. By the time you complete Lab 100, you will possess a portfolio project capable of demonstrating real-world engineering capability far beyond typical AI tutorial projects. Why Enroll Now? Agentic AI is rapidly becoming one of the most valuable engineering disciplines in the technology industry. The engineers who understand autonomous systems, MCP, RAG, LLMOps, governance, and enterprise deployment will help define the next generation of software. The opportunity is enormous. But the window to become an early expert will not remain open forever. If you want to move beyond prompting and learn how production-grade AI systems are actually built, this course provides the roadmap. Start your 100-lab journey today and build the skills required to engineer the future of autonomous AI systems. 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