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AI Agents, RAG & MCP: 7-Day Builder Bootcamp

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Build autonomous agents, advanced RAG systems, MCP servers, browser agents, and production-ready AI platforms.
1
1/5
(78) Ratings
115 students
Created by School of AI
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What you'll learn

  • Build autonomous AI agents capable of planning, reasoning, memory management, and tool execution.
  • Design and implement advanced RAG systems using hybrid retrieval, knowledge graphs, and agentic workflows.
  • Develop MCP servers that connect AI systems to databases, APIs, tools, and enterprise resources.
  • Create browser agents that navigate websites, automate workflows, and perform real-world tasks.
  • Architect and orchestrate multi-agent systems using LangGraph and modern agent communication patterns.
  • Build multimodal AI applications that combine text, images, documents, and voice interactions.
  • Implement AI evaluation, observability, monitoring, and governance practices for production systems.
  • Develop portfolio-ready AI applications using Python, FastAPI, vector databases, and modern AI frameworks.
  • Understand enterprise AI architecture patterns used in advanced AI products and platforms.
  • Gain hands-on experience building seven complete AI systems from scratch.
This course includes:
12 total hours on-demand video
0 articles
8 downloadable resources
36 lessons
Full lifetime access
Access on mobile and TV
Certificate of completion
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Course content

Requirements

  • Intermediate Python programming experience.
  • Basic understanding of APIs and JSON.
  • Familiarity with command-line tools and package management.
  • Prior exposure to AI, machine learning, or LLM applications is recommended.
  • A computer capable of running modern AI development tools.
  • Internet access for installing libraries and development frameworks.
  • Curiosity and willingness to build complex systems through hands-on projects.
  • No prior experience with agents, RAG, MCP, or LangGraph is required.
  • No advanced mathematics or machine learning background is necessary.
  • All projects are built step-by-step throughout the course.

Description

Artificial Intelligence is rapidly evolving beyond simple chatbots and prompt engineering. Modern organizations are building intelligent systems that can reason, plan, retrieve knowledge, use tools, automate workflows, browse websites, collaborate with other agents, and operate as autonomous digital workers. The demand for engineers who understand how to build these advanced systems has never been higher.

AI Agents, RAG & MCP: 7-Day Builder Bootcamp is an intensive, hands-on course designed for developers, AI engineers, architects, and technical professionals who already have experience with Python and basic AI development and want to master the next generation of AI systems.

Unlike courses that focus only on prompting or individual AI tools, this bootcamp teaches how to engineer complete AI applications from the ground up. Throughout seven action-packed days, you will build real-world projects using modern frameworks, architectures, and design patterns used by leading AI teams today.

You will begin by learning how to create Autonomous AI Agents capable of planning tasks, executing tools, storing memory, reflecting on results, and generating structured outputs. Next, you’ll dive into Advanced Retrieval-Augmented Generation (RAG), learning how to build enterprise-grade knowledge systems using Hybrid Retrieval, Knowledge Graphs, Agentic RAG, and source-grounded responses.

The course then explores the rapidly growing ecosystem around the Model Context Protocol (MCP). You will build reusable MCP servers, connect AI systems to databases and APIs, and learn how modern agents interact with external tools and resources.

You’ll also learn how to build Browser Agents that navigate websites, extract information, automate workflows, and operate as AI-powered digital workers. From there, you’ll move into Multi-Agent Systems, where specialized agents collaborate through orchestration frameworks such as LangGraph to solve complex business problems.

In the second half of the bootcamp, you’ll explore Multimodal AI, combining Text, Images, Documents, and Voice into intelligent applications capable of understanding and reasoning across multiple data types.

Finally, you’ll learn how professional AI teams evaluate, monitor, govern, and deploy AI systems using AI Evaluation Frameworks, Observability, Guardrails, FastAPI, and production engineering practices.

By the end of this course, you will have built seven portfolio-ready projects:

  • Autonomous Research Agent

  • Enterprise Knowledge Agent

  • Production MCP Server

  • Autonomous Browser Agent

  • Multi-Agent Business Intelligence System

  • Multimodal Operations Copilot

  • Production AI Platform

Whether your goal is to become an AI Engineer, Agent Engineer, Generative AI Developer, Solutions Architect, or technical leader, this course will provide practical experience building the kinds of systems organizations are actively deploying today.

If you’re ready to move beyond prompts and start building real AI Agents, RAG Systems, MCP Integrations, Multi-Agent Workflows, and Production AI Applications, this bootcamp is for you.

Who this course is for:

  • Software engineers looking to transition into AI engineering.
  • AI engineers who want to move beyond prompt engineering and chatbots.
  • Python developers interested in building production-grade AI applications.
  • Solutions architects exploring modern AI system design patterns.
  • Technical leads evaluating agentic AI architectures for their organizations.
  • Developers interested in RAG, MCP, browser automation, and multi-agent systems.
  • Professionals building internal AI tools, copilots, and intelligent workflows.
  • Startup founders creating AI-powered products and platforms.
  • Technology enthusiasts seeking hands-on experience with advanced AI systems.
  • Anyone wanting to build a portfolio of modern AI projects used in real-world environments.
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