This document provides a curated collection of high-quality resources for learning about AI, data science, and related topics from respected experts, researchers, and institutions. Resources are organised by topic, format, and expertise level for easy navigation.
This document provides a curated list of high-quality sources for learning about AI, data science, and related topics. These sources come from respected experts, researchers, and institutions, making them reliable and informative references. 📚 indicates an authoritative reference source.
This resource hub uses several navigation aids to help you quickly find relevant resources:
- By Topic: Find resources organised by subject area
- By Format: Browse resources by content type (books, courses, etc.)
- By Expertise Level: Filter resources by difficulty
- Tag Index: Find resources by specific topics or technologies
Each resource includes standardised metadata:
- Type: 📕 Book | 🎓 Course | 📄 Article | 📹 Talk | 📰 Newsletter | 🔍 Research | 👤 Person
- Level: 🟢 Beginner | 🟡 Intermediate | 🔴 Advanced
- Tags: Keywords for cross-referencing
- Description: Brief explanation of the resource's content and value
A selection of foundational resources that provide great value:
- Type: 🎓 Course 📚
- Level: 🟢 Beginner to 🟡 Intermediate
- Tags: #deep-learning #practical #hands-on #fastai
- Description: A rich, practice-oriented course that teaches how to apply deep learning to practical problems, complemented by the Fastbook.
- Type: 🎓 Course 📚
- Level: 🟡 Intermediate
- Tags: #llm #software-development #agents #evaluation #best-practices
- Description: Teaches how to build LLM-powered software reliably, from first principles, covering the entire GenAI software development lifecycle.
- Type: 📄 Article 📚
- Level: 🟡 Intermediate
- Tags: #llm #product-development #lessons-learned #applied-ai
- Description: Practical guide to building successful LLM products, covering tactical, operational, and strategic considerations, complemented by podcast episodes 29 and 30.
- Type: 🎓 Course 📚
- Level: 🟡 Intermediate to 🔴 Advanced
- Tags: #llm #agents #foundation-models #task-automation
- Description: Comprehensive course discussing fundamental concepts for LLM agents, including LLM foundations, essential abilities for task automation, and agent development infrastructure.
- Type: 🔍 Research
- Level: 🟢 Beginner to 🟡 Intermediate
- Tags: #data-visualisation #global-issues #research #evidence-based
- Description: Project from the University of Oxford providing data-driven insights into global issues, valuable for understanding the world's largest problems and potential solutions.
- Type: 📕 Book 📚
- Level: 🟡 Intermediate
- Tags: #machine-learning #supervised-learning #science #best-practices
- Description: Explores the role of supervised machine learning in scientific research with philosophical justifications and integration best practices.
- Type: 📕 Book 📚
- Level: 🟡 Intermediate
- Tags: #algorithms #optimisation #metaheuristics #stochastic
- Description: Open lecture notes on metaheuristic algorithms, covering stochastic optimisation methods intended as alternatives to brute-force search.
- Type: 📕 Book 📚
- Level: 🟢 Beginner to 🟡 Intermediate
- Tags: #genai #product-development #foundation-models #implementation
- Description: Comprehensive guide laying out the foundations for building products with Generative AI.
- Type: 📕 Book 📚
- Level: 🟢 Beginner to 🟡 Intermediate
- Tags: #llm #ollama #on-premise #privacy #function-calling #agents
- Description: Demonstrates how to run LLMs on-premise to maintain data privacy and control of your tech stack, with clear Python code examples.
- Type: 📄 Article 📚
- Level: 🟡 Intermediate to 🔴 Advanced
- Tags: #agents #llm #anthropic #agentic-workflow #alignment
- Description: Research paper exploring robust AI agent design, presenting agentic workflow approaches, alignment methods, and techniques for autonomous, reliable tasks.
- Type: 📄 Article 📚
- Level: 🟡 Intermediate
- Tags: #structured-output #llm #function-calling #parsing #json
- Description: Provides various solutions for achieving structured output from LLMs when function calling or specific response formats become challenging.
- Type: 📄 Article 📚
- Level: 🟢 Beginner to 🟡 Intermediate
- Tags: #embeddings #vector-representations #nlp #semantic-search
- Description: Comprehensive article exploring the concept of embeddings, their applications, and how they work in modern AI systems.
- Type: 📄 Article 📚
- Level: 🟡 Intermediate
- Tags: #evaluation #ai-testing #product-development #quality-assessment
- Description: Structured, comprehensive resource on how to construct domain-specific evaluation systems for AI products.
- Type: 📄 Article 📚
- Level: 🟡 Intermediate
- Tags: #data-flywheel #llm #logging #evaluation #continuous-improvement
- Description: Breaks down how to improve AI systems iteratively through logging, evaluation, and continuous refinement processes.
- Type: 📄 Article
- Level: 🟢 Beginner
- Tags: #mlops #devops #data-centric #production-systems
- Description: Explains how machine learning operations differ from traditional DevOps due to ML's direct exposure to messy real-world data.
- Type: 🔍 Research
- Level: 🟡 Intermediate
- Tags: #ai-engineering #papers #llm #benchmarks #prompting #rag #agents #code-generation
- Description: Curated list of 50 papers/models/blogs across 10 fields in AI Engineering, providing a solid foundation for understanding current research directions.
- Type: 👤 Person
- Level: 🟡 Intermediate to 🔴 Advanced
- Tags: #ai-ethics #complex-systems #computational-intelligence
- Description: Respected professor of computer science and prominent figure in complex systems and artificial intelligence, offering valuable perspectives on AI challenges.
- Type: 📹 Talk
- Level: 🟢 Beginner
- Tags: #presentations #communication #slides #public-speaking
- Description: Collection of excellent presentations on how to present effectively.
- Type: 📕 Book 📚
- Level: 🟢 Beginner
- Tags: #powerpoint #presentations #communication #visual-thinking
- Description: A book about PowerPoint built out of PowerPoint, covering communication techniques, culture, and effective presentation approaches.
- Type: 📹 Talk
- Level: 🟡 Intermediate to 🔴 Advanced
- Tags: #gpu-programming #cuda #flash-attention #triton #quantisation
- Description: Channel with excellent material on GPU programming, including CUDA kernels, Flash Attention, Triton, and quantisation techniques.
- Type: 📕 Book 📚
- Level: 🟡 Intermediate
- Tags: #machine-learning #supervised-learning #science #best-practices
- Description: Explores the role of supervised machine learning in scientific research with philosophical justifications and integration best practices.
- Type: 📕 Book 📚
- Level: 🟡 Intermediate
- Tags: #algorithms #optimisation #metaheuristics #stochastic
- Description: Open lecture notes on metaheuristic algorithms, covering stochastic optimisation methods intended as alternatives to brute-force search.
- Type: 📕 Book 📚
- Level: 🟢 Beginner to 🟡 Intermediate
- Tags: #llm #ollama #on-premise #privacy #function-calling #agents
- Description: Demonstrates how to run LLMs on-premise to maintain data privacy and control of your tech stack, with clear Python code examples.
- Type: 📕 Book 📚
- Level: 🟢 Beginner to 🟡 Intermediate
- Tags: #genai #product-development #foundation-models #implementation
- Description: Comprehensive guide laying out the foundations for building products with Generative AI.
- Type: 📕 Book 📚
- Level: 🟢 Beginner
- Tags: #powerpoint #presentations #communication #visual-thinking
- Description: A book about PowerPoint built out of PowerPoint, covering communication techniques, culture, and effective presentation approaches.
- Type: 🎓 Course 📚
- Level: 🟢 Beginner to 🟡 Intermediate
- Tags: #deep-learning #practical #hands-on #fastai
- Description: A rich, practice-oriented course that teaches how to apply deep learning to practical problems, complemented by the Fastbook.
- Type: 🎓 Course 📚
- Level: 🟡 Intermediate
- Tags: #llm #software-development #agents #evaluation #best-practices
- Description: Teaches how to build LLM-powered software reliably, from first principles, covering the entire GenAI software development lifecycle.
- Type: 🎓 Course 📚
- Level: 🟡 Intermediate to 🔴 Advanced
- Tags: #llm #agents #foundation-models #task-automation
- Description: Comprehensive course discussing fundamental concepts for LLM agents, including LLM foundations, essential abilities for task automation, and agent development infrastructure.
- Type: 📄 Article 📚
- Level: 🟡 Intermediate
- Tags: #evaluation #ai-testing #product-development #quality-assessment
- Description: Structured, comprehensive resource on how to construct domain-specific evaluation systems for AI products.
- Type: 📄 Article 📚
- Level: 🟡 Intermediate
- Tags: #data-flywheel #llm #logging #evaluation #continuous-improvement
- Description: Breaks down how to improve AI systems iteratively through logging, evaluation, and continuous refinement processes.
- Type: 📄 Article 📚
- Level: 🟡 Intermediate
- Tags: #llm #product-development #lessons-learned #applied-ai
- Description: Practical guide to building successful LLM products, covering tactical, operational, and strategic considerations, complemented by podcast episodes 29 and 30.
- Type: 📄 Article 📚
- Level: 🟡 Intermediate to 🔴 Advanced
- Tags: #agents #llm #anthropic #agentic-workflow #alignment
- Description: Research paper exploring robust AI agent design, presenting agentic workflow approaches, alignment methods, and techniques for autonomous, reliable tasks.
- Type: 📄 Article 📚
- Level: 🟢 Beginner to 🟡 Intermediate
- Tags: #embeddings #vector-representations #nlp #semantic-search
- Description: Comprehensive article exploring the concept of embeddings, their applications, and how they work in modern AI systems.
- Type: 📄 Article 📚
- Level: 🟡 Intermediate
- Tags: #structured-output #llm #function-calling #parsing #json
- Description: Provides various solutions for achieving structured output from LLMs when function calling or specific response formats become challenging.
- Type: 📄 Article
- Level: 🟢 Beginner
- Tags: #mlops #devops #data-centric #production-systems
- Description: Explains how machine learning operations differ from traditional DevOps due to ML's direct exposure to messy real-world data.
- Type: 📹 Talk
- Level: 🟢 Beginner
- Tags: #presentations #communication #slides #public-speaking
- Description: Collection of excellent presentations on how to present effectively.
- Type: 📹 Talk
- Level: 🟡 Intermediate
- Tags: #engineering-leadership #tech-solutions #workplace-politics #egoless-engineering
- Description: Insightful talks on egoless engineering, straightforward tech solutions, and workplace politics from an engineering leadership perspective.
- Type: 📹 Talk
- Level: 🟡 Intermediate to 🔴 Advanced
- Tags: #hacking #reverse-engineering #security #technical-exploration
- Description: Vast collection of presentations by the Chaos Computer Club, covering reverse engineering, cutting-edge exploration, and authentic engineering concepts.
- Type: 📹 Talk
- Level: 🟡 Intermediate to 🔴 Advanced
- Tags: #gpu-programming #cuda #flash-attention #triton #quantisation
- Description: Channel with excellent material on GPU programming, including CUDA kernels, Flash Attention, Triton, and quantisation techniques.
- Type: 📰 Newsletter
- Level: 🟢 Beginner to 🟡 Intermediate
- Tags: #ai-news #trends #research #development
- Description: Daily newsletter summarising top discussions in AI-focused online communities, covering latest trends, research, and developments.
- Type: 📰 Newsletter
- Level: 🟢 Beginner
- Tags: #ai-education #machine-learning #accessible-explanations
- Description: Newsletter by Professor Tom Yeh providing insights and educational content with accessible explanations of AI concepts.
- Type: 🔍 Research
- Level: 🟡 Intermediate to 🔴 Advanced
- Tags: #research-assistant #arxiv #computer-science #trending-papers
- Description: AI research assistant that synthesises the latest computer science research from arXiv and surfaces trending pre-prints.
- Type: 🔍 Research
- Level: 🟡 Intermediate
- Tags: #ai-engineering #papers #llm #benchmarks #prompting #rag #agents #code-generation
- Description: Curated list of 50 papers/models/blogs across 10 fields in AI Engineering, providing a solid foundation for understanding current research directions.
- Type: 🔍 Research
- Level: 🟢 Beginner to 🟡 Intermediate
- Tags: #data-visualisation #global-issues #research #evidence-based
- Description: Project from the University of Oxford providing data-driven insights into global issues, valuable for understanding the world's largest problems and potential solutions.
- Type: 👤 Person
- Level: 🟡 Intermediate
- Tags: #healthcare #medical-ai #future-medicine #technology
- Description: Renowned cardiologist, scientist, and author who has written extensively on the future of medicine, including AI and digital technologies impact.
- Type: 👤 Person
- Level: 🟡 Intermediate to 🔴 Advanced
- Tags: #data-science #fastai #deep-learning #ai-education
- Description: Prominent data scientist, co-founder of fast.ai and answer.ai, providing educational content and research insights in data science.
- Type: 👤 Person
- Level: 🟡 Intermediate
- Tags: #data-science #ai-ethics #ai-education #mathematics
- Description: Data scientist, educator, ethics advocate who co-founded fast.ai and directed USF's Center for Applied Data Ethics, recognised as one of Forbes' 20 Incredible Women in AI.
- Type: 👤 Person
- Level: 🟡 Intermediate to 🔴 Advanced
- Tags: #ai-research #deep-learning #tesla #openai
- Description: Leading AI researcher and educator, former Director of AI at Tesla and founding team member at OpenAI, providing in-depth insights on AI advancements.
- Type: 👤 Person
- Level: 🟡 Intermediate
- Tags: #open-source #datasette #django #data-tools
- Description: Independent open-source developer and data leader, creator of Datasette and co-creator of Django, with significant contributions to open-source community.
- Type: 👤 Person
- Level: 🟡 Intermediate to 🔴 Advanced
- Tags: #ai-ethics #complex-systems #computational-intelligence
- Description: Respected professor of computer science and prominent figure in complex systems and artificial intelligence, offering valuable perspectives on AI challenges.
- Type: 👤 Person
- Level: 🔴 Advanced
- Tags: #machine-learning #bayesian-optimisation #battery-modeling #quantum-devices
- Description: Professor of machine learning focused on Bayesian optimisation and applications in battery modeling and quantum devices, creator of Bluesky starter packs for prominent figures.
- Type: 👤 Person
- Level: 🟡 Intermediate
- Tags: #statistics #ml-interpretability #uncertainty-quantification #mindful-modeler
- Description: Statistician and ML expert specialising in interpretability and uncertainty quantification, author of books on interpretable ML and modeling mindsets.
- Type: 📹 Talk
- Level: 🟢 Beginner
- Tags: #presentations #communication #slides #public-speaking
- Description: Collection of excellent presentations on how to present effectively.
- Type: 📕 Book 📚
- Level: 🟢 Beginner
- Tags: #powerpoint #presentations #communication #visual-thinking
- Description: A book about PowerPoint built out of PowerPoint, covering communication techniques, culture, and effective presentation approaches.
- Type: 📄 Article
- Level: 🟢 Beginner
- Tags: #mlops #devops #data-centric #production-systems
- Description: Explains how machine learning operations differ from traditional DevOps due to ML's direct exposure to messy real-world data.
- Type: 📰 Newsletter
- Level: 🟢 Beginner
- Tags: #ai-education #machine-learning #accessible-explanations
- Description: Newsletter by Professor Tom Yeh providing insights and educational content with accessible explanations of AI concepts.
- Type: 📕 Book 📚
- Level: 🟡 Intermediate
- Tags: #machine-learning #supervised-learning #science #best-practices
- Description: Explores the role of supervised machine learning in scientific research with philosophical justifications and integration best practices.
- Type: 🎓 Course 📚
- Level: 🟡 Intermediate
- Tags: #llm #software-development #agents #evaluation #best-practices
- Description: Teaches how to build LLM-powered software reliably, from first principles, covering the entire GenAI software development lifecycle.
- Type: 📄 Article 📚
- Level: 🟡 Intermediate
- Tags: #evaluation #ai-testing #product-development #quality-assessment
- Description: Structured, comprehensive resource on how to construct domain-specific evaluation systems for AI products.
- Type: 📹 Talk
- Level: 🟡 Intermediate
- Tags: #engineering-leadership #tech-solutions #workplace-politics #egoless-engineering
- Description: Insightful talks on egoless engineering, straightforward tech solutions, and workplace politics from an engineering leadership perspective.
- Type: 🎓 Course 📚
- Level: 🟡 Intermediate to 🔴 Advanced
- Tags: #llm #agents #foundation-models #task-automation
- Description: Comprehensive course discussing fundamental concepts for LLM agents, including LLM foundations, essential abilities for task automation, and agent development infrastructure.
- Type: 📄 Article 📚
- Level: 🟡 Intermediate to 🔴 Advanced
- Tags: #agents #llm #anthropic #agentic-workflow #alignment
- Description: Research paper exploring robust AI agent design, presenting agentic workflow approaches, alignment methods, and techniques for autonomous, reliable tasks.
- Type: 📹 Talk
- Level: 🟡 Intermediate to 🔴 Advanced
- Tags: #gpu-programming #cuda #flash-attention #triton #quantisation
- Description: Channel with excellent material on GPU programming, including CUDA kernels, Flash Attention, Triton, and quantisation techniques.
- Type: 👤 Person
- Level: 🔴 Advanced
- Tags: #machine-learning #bayesian-optimisation #battery-modeling #quantum-devices
- Description: Professor of machine learning focused on Bayesian optimisation and applications in battery modeling and quantum devices, creator of Bluesky starter packs for prominent figures.
- #accessible-explanations: AI by Hand
- #agents: Building LLM Applications, CS294/194-196 Large Language Model Agents, Building Effective Agents, Ollama in Action, The 2025 AI Engineer Reading List
- #ai-education: AI by Hand, Rachel Thomas
- #ai-engineering: The 2025 AI Engineer Reading List
- #ai-ethics: Rachel Thomas, Melanie Mitchell
- #ai-news: AI News
- #ai-research: Andrej Karpathy
- #ai-testing: Your AI Product Needs Evals
- #algorithms: Essentials of Metaheuristics
- #alignment: Building Effective Agents
- #anthropic: Building Effective Agents
- #agentic-workflow: Building Effective Agents
- #applied-ai: What We've Learned From A Year of Building with LLMs
- #arxiv: Emergent Mind
- #bayesian-optimisation: Michael A. Osborne
- #battery-modeling: Michael A. Osborne
- #benchmarks: The 2025 AI Engineer Reading List
- #best-practices: Supervised Machine Learning for Science, Building LLM Applications
- #code-generation: The 2025 AI Engineer Reading List
- #communication: Doing presentations, Everything I Know About Life I Learned From PowerPoint
- #complex-systems: Melanie Mitchell
- #computational-intelligence: Melanie Mitchell
- #computer-science: Emergent Mind
- #continuous-improvement: Data Flywheels for LLM Applications
- #cuda: GPU MODE
- #data-centric: MLOps vs. DevOps: Why data makes it different
- #data-flywheel: Data Flywheels for LLM Applications
- #data-science: Jeremy Howard, Rachel Thomas
- #data-tools: Simon Willison
- #data-visualisation: Our World in Data
- #datasette: Simon Willison
- #deep-learning: Fast.ai's Practical Deep Learning, Jeremy Howard, Andrej Karpathy
- #development: AI News
- #devops: MLOps vs. DevOps: Why data makes it different
- #django: Simon Willison
- #egoless-engineering: The .CLUB Club
- #embeddings: What are Embeddings
- #engineering-leadership: The .CLUB Club
- #evaluation: Building LLM Applications, Your AI Product Needs Evals, Data Flywheels for LLM Applications
- #evidence-based: Our World in Data
- #fastai: Fast.ai's Practical Deep Learning, Jeremy Howard
- #flash-attention: GPU MODE
- #foundation-models: CS294/194-196 Large Language Model Agents, The GenAI Guidebook
- #function-calling: Ollama in Action, Every Way To Get Structured Output From LLMs
- #future-medicine: Eric Topol
- #genai: The GenAI Guidebook
- #global-issues: Our World in Data
- #gpu-programming: GPU MODE
- #hacking: ccc.de
- #hands-on: Fast.ai's Practical Deep Learning
- #healthcare: Eric Topol
- #implementation: The GenAI Guidebook
- #json: Every Way To Get Structured Output From LLMs
- #lessons-learned: What We've Learned From A Year of Building with LLMs
- #llm: Building LLM Applications, CS294/194-196 Large Language Model Agents, What We've Learned From A Year of Building with LLMs, Building Effective Agents, Ollama in Action, Data Flywheels for LLM Applications, Every Way To Get Structured Output From LLMs, The 2025 AI Engineer Reading List
- #logging: Data Flywheels for LLM Applications
- #machine-learning: Supervised Machine Learning for Science, AI by Hand, Michael A. Osborne
- #mathematics: Rachel Thomas
- #medical-ai: Eric Topol
- #metaheuristics: Essentials of Metaheuristics
- #mindful-modeler: Christoph Molnar
- #ml-interpretability: Christoph Molnar
- #mlops: MLOps vs. DevOps: Why data makes it different
- #nlp: What are Embeddings
- #on-premise: Ollama in Action
- #open-source: Simon Willison
- #openai: Andrej Karpathy
- #optimisation: Essentials of Metaheuristics
- #papers: The 2025 AI Engineer Reading List
- #parsing: Every Way To Get Structured Output From LLMs
- #powerpoint: Everything I Know About Life I Learned From PowerPoint
- #practical: Fast.ai's Practical Deep Learning
- #presentations: Doing presentations, Everything I Know About Life I Learned From PowerPoint
- #privacy: Ollama in Action
- #product-development: The GenAI Guidebook, What We've Learned From A Year of Building with LLMs, Your AI Product Needs Evals
- #production-systems: MLOps vs. DevOps: Why data makes it different
- #prompting: The 2025 AI Engineer Reading List
- #public-speaking: Doing presentations
- #quality-assessment: Your AI Product Needs Evals
- #quantisation: GPU MODE
- #quantum-devices: Michael A. Osborne
- #rag: The 2025 AI Engineer Reading List
- #research: AI News, Emergent Mind, Our World in Data
- #research-assistant: Emergent Mind
- #reverse-engineering: ccc.de
- #science: Supervised Machine Learning for Science
- #security: ccc.de
- #semantic-search: What are Embeddings
- #slides: Doing presentations
- #software-development: Building LLM Applications
- #statistics: Christoph Molnar
- #stochastic: Essentials of Metaheuristics
- #structured-output: Every Way To Get Structured Output From LLMs
- #supervised-learning: Supervised Machine Learning for Science
- #task-automation: CS294/194-196 Large Language Model Agents
- #tech-solutions: The .CLUB Club
- #technical-exploration: ccc.de
- #technology: Eric Topol
- #tesla: Andrej Karpathy
- #trends: AI News
- #trending-papers: Emergent Mind
- #triton: GPU MODE
- #uncertainty-quantification: Christoph Molnar
- #vector-representations: What are Embeddings
- #visual-thinking: Everything I Know About Life I Learned From PowerPoint
- #workplace-politics: The .CLUB Club