Agentic AI Courses
A complete AI-guided agentic AI curriculum
Ten courses covering the full range of agentic AI, from first principles to advanced topics. Each course is interactive, AI-guided, and available at adjustable difficulty levels.
Available courses
All 10 courses are fully interactive with AI chat, personas, and practice modes.
Introduction to Agentic AI
A broad, conceptual introduction to Agentic AI as a discipline. Explore what AI agents are, how they reason, plan, and act in the world, and why agentic systems represent a paradigm shift in how we build and deploy AI.
AI Fundamentals & Large Language Models
Understand the foundations of modern AI and the large language models (LLMs) that power agentic systems. Learn how neural networks learn, what makes LLMs special, and how they generate text one token at a time.
Prompt Engineering
Master the art and science of writing effective prompts. Learn how prompt structure, context, and framing dramatically affect model outputs, and explore advanced techniques like chain-of-thought, few-shot prompting, and system prompt design.
Tool Use & Function Calling
Learn how AI agents extend their capabilities through tools. Explore function calling APIs, tool design patterns, and how agents decide which tools to use and when — turning language models into systems that can act on the real world.
Agent Architectures
Survey the major architectural patterns for building AI agents. From simple ReAct loops to structured planning systems, learn how different architectures trade off capability, reliability, and interpretability.
Multi-Agent Systems
Explore the design and behavior of systems with multiple collaborating AI agents. Learn how agents communicate, coordinate, divide labor, and resolve conflicts — and how emergent behaviors arise when many agents interact.
Memory & Context Management
Learn how AI agents store, retrieve, and manage information across interactions. Explore the different types of agent memory — in-context, episodic, semantic, and procedural — and the techniques used to give agents effective long-term recall.
AI Safety & Alignment
Examine the core challenges of building AI systems that are safe, reliable, and aligned with human values. From prompt injection to reward hacking to long-term existential risk, develop a rigorous framework for thinking about AI safety.
Building Production Agents
Move from prototype to production. Learn the engineering practices required to build AI agents that are reliable, observable, cost-effective, and maintainable at scale — including evaluation, tracing, error handling, and CI/CD for AI systems.
Agentic AI in the Real World
Survey how agentic AI is being deployed across industries today. From software engineering and scientific research to healthcare and finance, examine real-world use cases, the lessons learned, and the challenges that remain unsolved.
Coming soon
These courses are in development.
Robotic Process Automation & AI Workflows
Automating business processes with AI-driven workflow orchestration.
Coming soonAI in Healthcare & Life Sciences
Applications of AI in diagnostics, drug discovery, and clinical workflows.
Coming soonAutonomous Vehicle Systems
AI perception, planning, and control systems for self-driving vehicles.
Coming soonAI Ethics & Governance
Frameworks and policies for responsible development and deployment of AI.
Coming soonGuided learning paths
Not sure where to start? Follow one of these curated learning paths.
I'm new to AI
Start from scratch and build a solid foundation in AI, from core concepts and large language models all the way to building your first agent.
- 1.Introduction to Agentic AI
- 2.AI Fundamentals & Large Language Models
- 3.Prompt Engineering
- 4.Tool Use & Function Calling
- 5.Agent Architectures
- 6.Multi-Agent Systems
- 7.Memory & Context Management
- 8.AI Safety & Alignment
- 9.Building Production Agents
- 10.Agentic AI in the Real World
I want to build my first agent
Jump straight into building. This path gives you the minimum foundation you need to build a working AI agent, then takes you step by step through the key engineering concepts.
- 1.Introduction to Agentic AI
- 2.Prompt Engineering
- 3.Tool Use & Function Calling
- 4.Agent Architectures
- 5.Building Production Agents
- →Pair with AI Fundamentals & LLMs for a deeper theoretical grounding.
I want to understand how LLMs work
Go deep on the technology behind large language models — from transformers and tokenization to training, fine-tuning, and alignment.
- 1.AI Fundamentals & Large Language Models
- 2.Prompt Engineering
- 3.Memory & Context Management
- 4.AI Safety & Alignment
I'm interested in AI safety
Explore the alignment problem, safety research, and the philosophical and technical challenges of building AI systems that are reliably beneficial.
- 1.Introduction to Agentic AI
- 2.AI Fundamentals & Large Language Models
- 3.Agent Architectures
- 4.AI Safety & Alignment
- 5.Agentic AI in the Real World
I'm deploying AI in production
A practitioner-focused path covering everything you need to build, evaluate, monitor, and maintain AI agents in real-world production environments.
- 1.Prompt Engineering
- 2.Tool Use & Function Calling
- 3.Agent Architectures
- 4.Memory & Context Management
- 5.Multi-Agent Systems
- 6.Building Production Agents
- 7.Agentic AI in the Real World