The most widely used structured course for getting into alignment, with curated readings progressing from core concepts to open research problems.
Courses
Free online courses and structured curricula for learning AI safety and alignment—from non-technical introductions to hands-on research engineering.
Browse this category in the interactive library →
Free online course building a working understanding of the major open problems in technical AI safety—alignment and RLHF, mechanistic interpretability, evaluations and red-teaming, AI control, and scalable oversight.
Free introductory online course replacing scattered articles with clear explanations of what is actually happening with AI and where it is headed, including interactive demos of cutting-edge systems.
Online follow-on program where graduates of the technical course work with an AI safety expert to produce a real contribution to the field and build a first portfolio piece in safety research or engineering.
Intensive online bootcamp preparing early-to-mid-career professionals for operational roles at organisations working to make AI go well.
Free, nonprofit AI safety course focused on misaligned superintelligence—why it is the central risk and why alignment is hard—delivered online with a 1-on-1 AI tutor, guided group discussions, and no application process.
Hands-on technical curriculum for skilling up in AI alignment research engineering, freely available online and covering deep learning fundamentals, transformer mechanistic interpretability, reinforcement learning, and LLM evaluations.
Dan Hendrycks' online course introducing students with a deep learning background to empirical ML safety research—robustness, monitoring, control, and systemic safety—with public lectures, readings, and coding assignments.
Fully online, non-technical CAIS course based on the textbook of the same name, covering how AI systems work, why advanced AI could pose societal-scale risks, and how society can manage and mitigate them—no prior ML experience required.