AI Agents

Learn how agent systems plan, use tools, keep context, and fail, with stronger treatment of boundaries, oversight, and traceability.

This course is for people who need to understand what agentic systems can really do and where the dangerous assumptions begin. By the end, you should be able to design agent workflows with explicit controls and explain why each decision was made.

20 hours6 stages, 25 modulesBeginners welcomeFree, no account

Start with Module 1

What you will learn

Build single and multi-agent AI systems from scratch
Deploy agents securely on local and cloud environments
Fine-tune open-source models for custom applications
Implement enterprise-grade security controls
Design scalable agentic architectures
Understand and mitigate AI security threats

Who this course is for

Non-technical professionals (GCSE level)
Small business owners
Teachers and educators
Developers and engineers
AI researchers and academics
Cybersecurity professionals

Prerequisites: None. Course starts from absolute basics

Course curriculum

Read the modules in order on the first pass. Use the practice and stage tests when you want a stricter check on what stuck.

Stage 1. Foundations

5 modules · 3 hours

1Understanding AI45 min 2From LLMs to Agents45 min 3Your Computer's Command Line30 min 4Setting Up Your Environment30 min 5Your First AI Interaction30 min PracticePractice testUntimed Stage testStage test15 min

Stage 2. Core concepts

5 modules · 4 hours

6How AI Agents Think60 min 7Tools and Actions45 min 8Memory and Context45 min 9Design Patterns45 min 10Architecture Fundamentals45 min

Stage 3. Practical building

5 modules · 5 hours

11Building Your First Agent60 min 12Multi-Agent Systems60 min 13Workflow Automation with n8n60 min 14Model Context Protocol (MCP)60 min 15Integration and APIs60 min PracticePractice testUntimed Stage testStage test15 min

Stage 4. Security and ethics

3 modules · 2 hours

16The Threat Landscape30 min 17Secure Implementation45 min 18Ethics and Responsible AI45 min

Stage 5. Advanced mastery

4 modules · 4 hours

19Fine-Tuning Open Source Models75 min 20Enterprise Architectures75 min 21Production Deployment45 min 22Research Frontiers45 min PracticePractice testUntimed Stage testStage test15 min

Stage 6. Capstone and certification

3 modules · 2 hours

23Capstone Project75 min 24Peer Review and Certification30 min 25Architecture Challenge Game15 min PracticePractice testUntimed Stage testStage test15 min

Standards and references

This course is aligned to the following standards, frameworks, and certification objectives.

1OWASP Top 10 for LLM and Generative AI Applications (2025)
2OWASP Top 10 for Agentic Applications (published 2025-12-09)
3NIST AI Risk Management Framework (AI RMF 1.0)
4NIST AI RMF companion guidance and resources
5ISO/IEC 42001:2023 AI management systems
6Model Context Protocol specification (2025-11-25)
7UK AI Cyber Security Code of Practice
8EU AI Act official timeline and phased obligations

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AI Agents

Learn how agent systems plan, use tools, keep context, and fail, with stronger treatment of boundaries, oversight, and traceability.

20 hours6 stages, 25 modulesBeginners welcomeFree, no account

Start with Module 1

What you will learn

Build single and multi-agent AI systems from scratch
Deploy agents securely on local and cloud environments
Fine-tune open-source models for custom applications
Implement enterprise-grade security controls
Design scalable agentic architectures
Understand and mitigate AI security threats

Who this course is for

Non-technical professionals (GCSE level)
Small business owners
Teachers and educators
Developers and engineers
AI researchers and academics
Cybersecurity professionals

Prerequisites: None. Course starts from absolute basics

Course curriculum

Read the modules in order on the first pass. Use the practice and stage tests when you want a stricter check on what stuck.

Stage 1. Foundations

5 modules · 3 hours

Stage 2. Core concepts

5 modules · 4 hours

6How AI Agents Think60 min 7Tools and Actions45 min 8Memory and Context45 min 9Design Patterns45 min 10Architecture Fundamentals45 min

Stage 3. Practical building

5 modules · 5 hours

Stage 4. Security and ethics

3 modules · 2 hours

16The Threat Landscape30 min 17Secure Implementation45 min 18Ethics and Responsible AI45 min

Stage 5. Advanced mastery

4 modules · 4 hours

19Fine-Tuning Open Source Models75 min 20Enterprise Architectures75 min 21Production Deployment45 min 22Research Frontiers45 min PracticePractice testUntimed Stage testStage test15 min

Stage 6. Capstone and certification

3 modules · 2 hours

23Capstone Project75 min 24Peer Review and Certification30 min 25Architecture Challenge Game15 min PracticePractice testUntimed Stage testStage test15 min

Standards and references

This course is aligned to the following standards, frameworks, and certification objectives.

1OWASP Top 10 for LLM and Generative AI Applications (2025)
2OWASP Top 10 for Agentic Applications (published 2025-12-09)
3NIST AI Risk Management Framework (AI RMF 1.0)
4NIST AI RMF companion guidance and resources
5ISO/IEC 42001:2023 AI management systems
6Model Context Protocol specification (2025-11-25)
7UK AI Cyber Security Code of Practice
8EU AI Act official timeline and phased obligations