Building AI systems that actually work. A grounded, practical course on agents, automation and orchestration — without the hype, without the jargon, and with real working examples you can build yourself.
Grounded, practical agent and automation knowledge — deliberately anti-hype.
What agents actually are, the difference between chatbots, workflows and autonomous agents.
Step-by-step construction, testing, iteration and common pitfalls to avoid.
What RAG is, when to use it, document processing and vector databases made simple.
Agent swarms, orchestration patterns, handoffs and coordination strategies.
Zapier, Make, n8n, custom scripts — when to use what and integration patterns.
Guardrails, human-in-the-loop, monitoring and responsible deployment.
Mapping processes, identifying automation candidates and designing reliable systems.
Complete build-alongs: research agent, content pipeline, customer service system.
9 modules cutting through the hype with grounded, practical knowledge.
4 lessons
5 lessons
5 lessons
5 lessons
4 lessons
5 lessons
4 lessons
4 lessons
5 lessons
Technically curious professionals wanting to understand agents (no coding required).
Business analysts and operations managers exploring process automation.
Developers wanting structured, practical agent knowledge beyond tutorials.
Innovation teams evaluating AI automation opportunities for their organisations.
Filmmaker turned AI educator with years of experience teaching AI and creating AI courses enjoyed by thousands of students. Rupert builds working agent systems, not theoretical frameworks — his deliberately anti-hype approach cuts through the noise to deliver practical, honest knowledge about what agents can and can't do today.
No. The course is designed for technically curious people who may not be developers. Many of the tools and platforms covered — Zapier, Make, n8n — use visual interfaces. Where code does appear, it’s explained step by step. Developers will find the structured approach valuable, but coding is not a prerequisite.
You should be comfortable using AI chatbots like ChatGPT or Claude, and have a basic grasp of concepts like prompting, tokens, and context windows. If you’ve been using AI regularly for a few months, or you’ve completed a fundamentals-level AI course, you’re ready. You don’t need any background in automation or programming.
The opposite. This course is deliberately anti-hype. It teaches you what agents actually can and can’t do today, when simpler automation is the better choice, and how to evaluate the many overblown claims in this space. If you want honest, grounded knowledge rather than breathless predictions about autonomous AI, this is the right course.
You’ll build real, working systems. Module 3 walks you through your first agent, and Module 9 contains four complete build-along projects: a research agent, a content pipeline, a customer service system, and a data analyst. These are functional systems you can adapt for your own needs, not toy demos.
The course covers the full automation stack: Zapier, Make, and n8n for workflow automation, plus multiple agent frameworks for building AI agents. Rather than going deep on one platform, the focus is on understanding patterns and architectures that transfer across tools — so your knowledge stays relevant as the landscape shifts.
Mastering AI Tools gives you broad, practical capability across the full AI landscape — prompting, image generation, vibe coding, and more. This course goes deep on one specific area: building AI agents and automation systems. There’s some natural overlap in the automation modules, but this course covers agent architecture, RAG, multi-agent systems, and safety frameworks in much more depth. Many students take both.
Module 8 covers the practical side of deploying agents responsibly: what can go wrong, how to set guardrails, how to monitor agent behaviour, and how to build governance frameworks that satisfy both technical and organisational requirements. This isn’t abstract ethics — it’s the operational knowledge you need before putting agents into production.
The course covers nine modules with build-along projects throughout. The projects in Module 9 take the most time, but they’re also where the deepest learning happens. For the fastest results, join a live lesson where Rupert guides you through the material with real-time support — contact us to find out when the next one runs.
Most of the platforms covered have free tiers that are sufficient for the course exercises. Some tools may require a paid plan if you want to use them at scale after the course, but the lessons are designed so you can follow along without spending money on subscriptions.
Very much so. The course is structured to give you both the technical understanding and the strategic framing to propose and implement AI automation within an organisation. The workflow design module and the build-along projects are specifically chosen because they map to common business needs — research, content, customer service, and data analysis.
The live lesson is $220 AUD ($150 USD) per person for the course. It covers the same core material in an instructor-led format with real-time Q&A, group exercises, and direct feedback from Rupert.
Contact us to find out about the next live lesson.
AI Educator · Filmmaker · Author of The AI-Native Playbook
Rupert has trained thousands of professionals across corporate workshops, online courses, and live intensives — turning complex AI concepts into practical, immediately applicable skills. As an filmmaker and creative technologist, he brings a unique perspective that bridges technical capability and real-world application.
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