AI Agent Engineering: Build Production-Ready AI Agents

Course Overview

This 21-day practical course guides learners from the fundamentals of AI applications to advanced AI agent systems. It covers building AI agents with capabilities such as memory, tools, Retrieval-Augmented Generation (RAG), planning, Model Context Protocol (MCP), multi-agent systems, orchestration, and deployment. Frameworks like LangGraph, CrewAI, and LangChain are used to develop production-ready AI agents. The course culminates in building an AI Research Agent and a Research AI Agent Platform.

Key Takeaways

• Build AI agents from scratch using Python and understand their core architecture.
• Create AI assistants with conversation memory, tool usage, document processing, and RAG.
• Design autonomous AI agents with planning, reasoning, memory, and advanced RAG capabilities.
• Integrate AI agents using MCP and connect them to external tools and data sources.
• Design and orchestrate multi-agent systems to solve complex problems collaboratively.
• Use LangGraph, CrewAI, and LangChain to build production-ready AI agents.
• Develop a complete AI Research Agent capable of researching, verifying, note-taking, and report generation.
• Deploy AI agent applications and build a Research AI Agent Platform as a capstone project.

Prerequisites

• No prior experience with AI agents, RAG, MCP, LangGraph, CrewAI, or LangChain is required.
• Basic familiarity with computers and willingness to learn programming is sufficient.
• No advanced Python knowledge needed; fundamentals are introduced as required.
• A computer with stable internet connection is necessary for practical exercises.
• Willingness to write code, experiment, and build real AI applications throughout the course.

Target Learners

• Beginners interested in building AI agents and AI-powered applications from scratch.
• Python learners and developers aiming to build practical AI systems.
• Software developers and engineers seeking to understand modern AI agent architecture including RAG, memory, planning, MCP, and multi-agent systems.
• AI and machine learning enthusiasts wanting hands-on experience with autonomous and production-ready AI agents.
• Students and professionals interested in learning AI agent frameworks such as LangGraph, CrewAI, and LangChain through projects.
• Anyone motivated to learn by building real-world AI projects including a complete AI Research Agent and Research AI Agent Platform.