A ROUTE THROUGH YOUR NEXT SKILL
Learning paths
Follow a clear sequence, see which courses are open today, and know what is still in preparation.
Paths are learning guides. "Planned" courses are not published or available to enrol in.
4 OF 4 COURSES AVAILABLE
Curious beginners and people bringing AI into study or work.
By the end: Build a thoughtful everyday AI workflow, then learn to check its limits and use language models well.
- Introduction to LLMsOpen now
- AI for Everyone: Learn, Create & Work SmarterOpen now
- AI Foundations & Responsible AIOpen now
- Large Language Models: From Prompts to PracticeOpen now
View this path →2 OF 2 COURSES AVAILABLE
Learners ready to move from programming basics to practical prediction.
By the end: Work with data in Python, then train and evaluate a reproducible machine learning model.
- Python & Data for Machine LearningOpen now
- Applied Machine Learning: Build, Evaluate, ImproveOpen now
View this path →5 OF 5 COURSES AVAILABLE
Aspiring developers who want a grounded route into language model engineering.
By the end: Build an evidence-based LLM application, then extend it into a bounded tool-using workflow.
- Introduction to LLMsOpen now
- Python & Data for Machine LearningOpen now
- Large Language Models: From Prompts to PracticeOpen now
- LLM Engineering: RAG, Evals & Multimodal AppsOpen now
- Agentic AI: Tools, Workflows & MCPOpen now
View this path →4 OF 4 COURSES AVAILABLE
Developers who can already call an LLM and want to ship reliable, tool-using agents.
By the end: Ship an MCP-connected agent with least-privilege tools, approval gates, an eval suite and a prompt-injection threat model.
- LLM Engineering: RAG, Evals & Multimodal AppsOpen now
- Agentic AI: Tools, Workflows & MCPOpen now
- Reasoning Models & Test-Time ComputeOpen now
- AI Safety & Alignment for BuildersOpen now
View this path →5 OF 5 COURSES AVAILABLE
Engineers, researchers and analysts who want to understand how frontier models are trained, measured and aligned.
By the end: Read a model release or paper critically: what training changed, what the evals really measure, and which safety claims are supported.
- Introduction to LLMsOpen now
- Post-Training: Fine-Tuning, RLHF & DPOOpen now
- Reasoning Models & Test-Time ComputeOpen now
- LLM Engineering: RAG, Evals & Multimodal AppsOpen now
- AI Safety & Alignment for BuildersOpen now
View this path →