Learn AI Agents course Syllabus
Full curriculum breakdown — modules, lessons, estimated time, and outcomes.
Overview: This course provides a practical introduction to AI agents, exploring how they leverage large language models and modern AI frameworks to automate tasks and solve complex problems. Learners will understand the architecture, reasoning, and real-world applications of AI agents, differentiating them from traditional chatbots. The curriculum covers core components such as memory, planning, tool integration, and multi-step workflows. With a total time commitment of approximately 8–12 weeks, this course blends conceptual understanding with hands-on implementation, culminating in a final project where learners build a functional AI agent.
Module 1: Introduction to AI Agents
Estimated time: 6 hours
- Define AI agents and their role in modern automation
- Compare AI agents with traditional chatbots
- Understand how large language models power agent intelligence
- Explore real-world use cases in productivity and customer service
Module 2: AI Agent Architecture & Components
Estimated time: 10 hours
- Break down the internal structure of AI agent systems
- Explain how agents process inputs and generate responses
- Understand context management and conversation persistence
- Design basic agent workflows for task execution
Module 3: Tool Integration & Workflow Automation
Estimated time: 10 hours
- Connect AI agents to external APIs and services
- Enable agents to retrieve data and perform actions
- Build automated workflows using agent logic
- Apply AI agents to improve task efficiency and productivity
Module 4: Multi-Step Reasoning & Decision Making
Estimated time: 10 hours
- Implement multi-step reasoning in AI agents
- Enable planning and sequential task execution
- Handle errors and improve system reliability
- Optimize responses for accuracy and relevance
Module 5: Final Project
Estimated time: 8 hours
- Design an AI agent for a specific automation task
- Implement reasoning, memory, and tool integration
- Test, refine, and demonstrate agent performance
Prerequisites
- Basic understanding of artificial intelligence concepts
- Familiarity with generative AI and language models
- Introductory knowledge of programming and APIs (helpful but not required)
What You'll Be Able to Do After
- Explain how AI agents differ from rule-based chatbots
- Describe the core architecture and components of AI agents
- Design and build agents that automate real-world tasks
- Integrate AI agents with external tools and APIs
- Demonstrate AI agent development through a working prototype