Understand the technology
Build a reliable mental model of LLMs, data, models and the limits of AI systems.
Start with the foundationsBuild practical AI skills, create working projects, and learn to test, secure and govern the systems you use.
AI capability is more than knowing the terminology. Learn how systems work, build with them, test their limits and make informed decisions about their use.
Build a reliable mental model of LLMs, data, models and the limits of AI systems.
Start with the foundationsTurn concepts into workflows, applications and AI-powered tools you can explain.
Explore applied AIUse structured tests to expose weaknesses, evaluate behaviour and improve reliability.
Explore AI securityTranslate technical understanding into risk assessments, controls and accountable decisions.
Explore AI governanceStart with the fundamentals or go straight to the discipline you need. Each path is built around practical skills and applied work.
Prompt design, context management, structured outputs and LLM evaluation
LLM security testing, prompt injection, adversarial evaluation and mitigation
Data labeling, annotation quality, evaluation rubrics and dataset review
AI risk assessments, control mapping, policy review and governance frameworks
AI portfolio projects, role mapping, practical skills and job-search preparation
AI workflows, tool use, API integrations and agent evaluation
AI engineering, LLM red teaming, guardrails, risk assessment and governance
No spam. No upsells. Just useful AI career intel.