A 15-module deep dive into how AI systems actually work — written for professionals who want genuine technical understanding. Covers LLMs and decoding, the model landscape, system architecture, RAG and advanced retrieval, prompting, context engineering, agents and agent protocols, hardware, cost, data privacy, safety, governance, evaluation, fine-tuning and distillation, and LLMops.
Find out where AI can save your business the most time. Select your industry and business areas, optionally enter your website URL, and get a tailored automation roadmap with specific tools and a prioritised action plan.
A curated directory of AI tools organised by use case. Find the right tool across 18 categories including writing, coding, research, productivity, image generation, video, audio, automation, design, legal, social media, and more.
Find out how exposed your role is to AI automation. Enter your job title, seniority, company size, and location to get a personalised risk score, task-by-task breakdown, career pivot suggestions, and actionable advice.
A 6-part series of hands-on Jupyter notebooks covering advanced data science topics including unsupervised learning, probabilistic modeling, neural networks, CNNs, sequence models, and transformers. The sequel to Data Science: Part 1.
A 6-part series of hands-on Jupyter notebooks that progressively teaches data science from Python fundamentals through advanced machine learning models including regression, classification, and ensemble methods.
An 8-week structured curriculum covering AI Safety and Alignment. Covers machine learning foundations, alignment challenges, interpretability, control methods, red-teaming, and governance. Designed for self-study or fellowship preparation.