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Build Autonomous AI Systems in 4 Weeks

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From Your First AI Agent to Production-Ready Multi-Agent Systems
1
1/5
(84) Ratings
222 students
Created by School of AI
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What you'll learn

  • Understand the architecture and lifecycle of modern AI agents and Agentic AI systems.
  • Build AI agents that can reason, plan, use tools, call APIs, and complete multi-step tasks.
  • Create agents with short-term memory, long-term memory, embeddings, and vector databases.
  • Build Retrieval-Augmented Generation (RAG) applications that answer questions from documents and PDFs.
  • Design autonomous research agents that search, analyze information, and generate structured reports.
  • Develop multi-agent systems using Planner, Executor, Researcher, Writer, and Reviewer roles.
  • Connect AI agents to APIs, databases, webhooks, files, and external business systems.
  • Build interactive AI interfaces using Streamlit, FastAPI, streaming responses, and optional voice capabilities.
  • Implement reflection, self-correction, evaluation, and LLM-as-judge workflows.
  • Add guardrails, validation checks, human approvals, logging, and governance controls.
  • Design event-driven and trigger-based autonomous workflows.
  • Build a Personal AI Operating System with connected agents and shared memory.
  • Deploy AI applications and prepare them for real-world production environments.
  • Create a portfolio-ready capstone with documentation, architecture diagrams, deployment, and a demo video.
This course includes:
16.5 total hours on-demand video
0 articles
14 downloadable resources
47 lessons
Full lifetime access
Access on mobile and TV
Certificate of completion
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Course content

Requirements

  • No previous AI agent or Agentic AI experience is required.
  • Basic familiarity with computers, files, folders, and installing software is recommended.
  • Basic Python knowledge is helpful, but the major concepts and implementation steps are explained throughout the course.
  • A Windows, macOS, or Linux computer capable of running Python applications.
  • A reliable internet connection for downloading tools, libraries, and course resources.
  • Python 3.10 or later installed on your computer.
  • A code editor such as Visual Studio Code.
  • Access to an AI model through OpenAI, Claude, Ollama, or another supported provider.
  • A willingness to experiment, troubleshoot, and build practical projects.
  • Optional familiarity with APIs, GitHub, command-line tools, or web development may be useful but is not required.
  • No advanced mathematics, machine learning degree, or data science background is necessary.

Description

Move beyond basic chatbots and learn how to design, build, and deploy intelligent systems that can plan, use tools, access knowledge, collaborate with other agents, and complete complex tasks autonomously.

Build Autonomous AI Systems in 4 Weeks is a fast-paced, project-driven bootcamp designed to take you from your first AI agent to sophisticated, production-ready multi-agent systems. Through live instruction, practical demonstrations, weekly assignments, and portfolio projects, you will develop the technical and architectural skills required to build real-world Agentic AI applications.

During the first week, you will explore the foundations of AI agents, including the differences between traditional Large Language Models, chatbots, workflows, and autonomous systems. You will learn how agents combine planning, memory, tools, reasoning, and actions to accomplish goals. You will build a personal AI assistant, a multi-tool agent, a PDF question-answering system, and an autonomous research agent.

The second week focuses on transforming prototypes into practical AI applications. You will design multi-agent workflows using architectures such as Planner, Executor, Researcher, Writer, and Reviewer. You will connect agents to REST APIs, databases, webhooks, file systems, and external business services. You will also build interactive interfaces with Streamlit, create streaming chat experiences, explore voice-enabled agents, and learn the foundations of deploying AI applications.

In week three, you will advance into autonomous intelligence at scale. Topics include Tree of Thoughts, reflection loops, self-correction, prompt chaining, event-driven automation, persistent agents, and AI self-evaluation. You will also learn how to introduce guardrails, validation checks, human approvals, audit logs, and governance controls into your systems. By the end of the week, you will build a prototype Personal AI Operating System with multiple connected agents and shared memory.

The final week is dedicated to building and presenting a portfolio-ready capstone. You may create an autonomous business agent, AI research copilot, coding agent, recruiting system, sales assistant, content factory, or workflow automation platform. You will optimize performance, improve prompts, prepare architecture diagrams, document your project, deploy your application, and create a compelling demo video.

Throughout the bootcamp, you will work with technologies such as Python, FastAPI, LangChain, LangGraph, CrewAI, ChromaDB, FAISS, OpenAI or Claude models, and modern deployment platforms. You will develop an understanding of Retrieval-Augmented Generation, embeddings, vector databases, structured outputs, tool calling, shared memory, and agent orchestration.

This bootcamp is beginner-friendly, but the outcomes are ambitious. Basic programming familiarity is useful, but every major concept is introduced through practical implementation.

By the end of the four weeks, you will have multiple working AI portfolio projects, a deployed capstone application, a documented GitHub portfolio, reusable production workflows, and the confidence to design autonomous AI systems for startups, enterprises, clients, or your own products.

Join the bootcamp and start building the next generation of AI agents, AI copilots, autonomous workflows, and intelligent digital teams.

Who this course is for:

  • Beginners who want to move beyond using chatbots and start building complete AI applications.
  • Python developers who want to specialize in AI agents, RAG, autonomous workflows, and multi-agent systems.
  • Software engineers who want practical experience with LangChain, LangGraph, CrewAI, FastAPI, and vector databases.
  • AI enthusiasts who want to understand how autonomous agents plan, use tools, remember information, and complete tasks.
  • Entrepreneurs and startup founders who want to prototype AI products, copilots, automation platforms, and digital workers.
  • Product managers and technical leaders who want to understand the architecture and capabilities of Agentic AI systems.
  • Automation professionals who want to connect AI agents to APIs, databases, webhooks, and business processes.
  • Freelancers and consultants who want to build AI solutions for clients and strengthen their technical portfolios.
  • Career changers seeking hands-on projects that demonstrate practical AI engineering skills.
  • Professionals who want to create a GitHub portfolio, deployed applications, architecture diagrams, and shareable demo videos.
  • Anyone interested in building production-ready AI agents instead of only learning theoretical AI concepts.
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