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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>AI Resource Hub - Just-in-Time Learning</title>
<link rel="stylesheet" href="/style.css">
</head>
<body>
<header>
<div class="container">
<h1>Just-in-Time Learning</h1>
<p class="subtitle">Curious. Simplicity ⟹ Reliability. V ↑ → Q ↓</p>
<nav>
<a href="/" class="back-link">← Back to Home</a>
</nav>
</div>
</header>
<main class="post-container">
<article class="post">
<header class="post-header">
<h1>AI Resource Hub</h1>
<span class="post-date"></span>
</header>
<div class="post-content">
<p>
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.</p>
<p>
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.</p>
<h2>
Table of Contents</h2>
<ul>
<li>
<a href="#how-to-use-this-hub">How to Use This Hub</a> </li>
<li>
<a href="#featured-resources">Featured Resources</a> </li>
<li>
<a href="#by-topic">By Topic</a> <ul>
<li>
<a href="#foundations-of-ai-and-ml">Foundations of AI and ML</a> </li>
<li>
<a href="#large-language-models">Large Language Models</a> </li>
<li>
<a href="#ai-engineering">AI Engineering</a> </li>
<li>
<a href="#data-science">Data Science</a> </li>
<li>
<a href="#ethics-and-responsible-ai">Ethics and Responsible AI</a> </li>
<li>
<a href="#technical-skills">Technical Skills</a> </li>
</ul>
</li>
<li>
<a href="#by-format">By Format</a> <ul>
<li>
<a href="#books">Books</a> </li>
<li>
<a href="#courses">Courses</a> </li>
<li>
<a href="#articles">Articles</a> </li>
<li>
<a href="#talks-and-presentations">Talks and Presentations</a> </li>
<li>
<a href="#newsletters">Newsletters</a> </li>
<li>
<a href="#research-resources">Research Resources</a> </li>
<li>
<a href="#social-media">Social Media</a> </li>
</ul>
</li>
<li>
<a href="#by-expertise-level">By Expertise Level</a> <ul>
<li>
<a href="#beginner">Beginner</a> </li>
<li>
<a href="#intermediate">Intermediate</a> </li>
<li>
<a href="#advanced">Advanced</a> </li>
</ul>
</li>
<li>
<a href="#tag-index">Tag Index</a> </li>
</ul>
<h2>
How to Use This Hub</h2>
<p>
This resource hub uses several navigation aids to help you quickly find relevant resources:</p>
<ul>
<li>
<strong>By Topic</strong>: Find resources organised by subject area </li>
<li>
<strong>By Format</strong>: Browse resources by content type (books, courses, etc.) </li>
<li>
<strong>By Expertise Level</strong>: Filter resources by difficulty </li>
<li>
<strong>Tag Index</strong>: Find resources by specific topics or technologies </li>
</ul>
<p>
Each resource includes standardised metadata:</p>
<ul>
<li>
<strong>Type</strong>: 📕 Book | 🎓 Course | 📄 Article | 📹 Talk | 📰 Newsletter | 🔍 Research | 👤 Person </li>
<li>
<strong>Level</strong>: 🟢 Beginner | 🟡 Intermediate | 🔴 Advanced </li>
<li>
<strong>Tags</strong>: Keywords for cross-referencing </li>
<li>
<strong>Description</strong>: Brief explanation of the resource’s content and value </li>
</ul>
<h2>
Featured Resources</h2>
<p>
A selection of foundational resources that provide great value:</p>
<h3>
<a href="https://course.fast.ai/">Fast.ai’s Practical Deep Learning</a></h3>
<ul>
<li>
<strong>Type:</strong> 🎓 Course 📚 </li>
<li>
<strong>Level:</strong> 🟢 Beginner to 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #deep-learning #practical #hands-on #fastai </li>
<li>
<strong>Description:</strong> A rich, practice-oriented course that teaches how to apply deep learning to practical problems, complemented by the <a href="https://github.com/fastai/fastbook">Fastbook</a>. </li>
</ul>
<h3>
<a href="https://xcancel.com/hugobowne/status/1870978490574704812">Building LLM Applications</a></h3>
<ul>
<li>
<strong>Type:</strong> 🎓 Course 📚 </li>
<li>
<strong>Level:</strong> 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #llm #software-development #agents #evaluation #best-practices </li>
<li>
<strong>Description:</strong> Teaches how to build LLM-powered software reliably, from first principles, covering the entire GenAI software development lifecycle. </li>
</ul>
<h3>
<a href="https://applied-llms.org/">What We’ve Learned From A Year of Building with LLMs</a></h3>
<ul>
<li>
<strong>Type:</strong> 📄 Article 📚 </li>
<li>
<strong>Level:</strong> 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #llm #product-development #lessons-learned #applied-ai </li>
<li>
<strong>Description:</strong> Practical guide to building successful LLM products, covering tactical, operational, and strategic considerations, complemented by podcast episodes <a href="https://vanishinggradients.fireside.fm/29">29</a> and <a href="https://vanishinggradients.fireside.fm/30">30</a>. </li>
</ul>
<h3>
<a href="https://rdi.berkeley.edu/llm-agents/f24">CS294/194-196 Large Language Model Agents</a></h3>
<ul>
<li>
<strong>Type:</strong> 🎓 Course 📚 </li>
<li>
<strong>Level:</strong> 🟡 Intermediate to 🔴 Advanced </li>
<li>
<strong>Tags:</strong> #llm #agents #foundation-models #task-automation </li>
<li>
<strong>Description:</strong> Comprehensive course discussing fundamental concepts for LLM agents, including LLM foundations, essential abilities for task automation, and agent development infrastructure. </li>
</ul>
<h3>
<a href="https://ourworldindata.org/">Our World in Data</a></h3>
<ul>
<li>
<strong>Type:</strong> 🔍 Research </li>
<li>
<strong>Level:</strong> 🟢 Beginner to 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #data-visualisation #global-issues #research #evidence-based </li>
<li>
<strong>Description:</strong> Project from the University of Oxford providing data-driven insights into global issues, valuable for understanding the world’s largest problems and potential solutions. </li>
</ul>
<h2>
By Topic</h2>
<h3>
Foundations of AI and ML</h3>
<h4>
Machine Learning Fundamentals</h4>
<h5>
<a href="https://ml-science-book.com/">Supervised Machine Learning for Science</a></h5>
<ul>
<li>
<strong>Type:</strong> 📕 Book 📚 </li>
<li>
<strong>Level:</strong> 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #machine-learning #supervised-learning #science #best-practices </li>
<li>
<strong>Description:</strong> Explores the role of supervised machine learning in scientific research with philosophical justifications and integration best practices. </li>
</ul>
<h4>
Algorithms and Optimisation</h4>
<h5>
<a href="https://cs.gmu.edu/~sean/book/metaheuristics/">Essentials of Metaheuristics</a></h5>
<ul>
<li>
<strong>Type:</strong> 📕 Book 📚 </li>
<li>
<strong>Level:</strong> 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #algorithms #optimisation #metaheuristics #stochastic </li>
<li>
<strong>Description:</strong> Open lecture notes on metaheuristic algorithms, covering stochastic optimisation methods intended as alternatives to brute-force search. </li>
</ul>
<h3>
Large Language Models</h3>
<h4>
Development and Applications</h4>
<h5>
<a href="https://ravinkumar.com/GenAiGuidebook/book_intro.html">The GenAI Guidebook</a></h5>
<ul>
<li>
<strong>Type:</strong> 📕 Book 📚 </li>
<li>
<strong>Level:</strong> 🟢 Beginner to 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #genai #product-development #foundation-models #implementation </li>
<li>
<strong>Description:</strong> Comprehensive guide laying out the foundations for building products with Generative AI. </li>
</ul>
<h5>
<a href="https://leanpub.com/ollama">Ollama in Action</a></h5>
<ul>
<li>
<strong>Type:</strong> 📕 Book 📚 </li>
<li>
<strong>Level:</strong> 🟢 Beginner to 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #llm #ollama #on-premise #privacy #function-calling #agents </li>
<li>
<strong>Description:</strong> Demonstrates how to run LLMs on-premise to maintain data privacy and control of your tech stack, with clear Python code examples. </li>
</ul>
<h4>
Agents</h4>
<h5>
<a href="https://www.anthropic.com/engineering/building-effective-agents">Building Effective Agents</a></h5>
<ul>
<li>
<strong>Type:</strong> 📄 Article 📚 </li>
<li>
<strong>Level:</strong> 🟡 Intermediate to 🔴 Advanced </li>
<li>
<strong>Tags:</strong> #agents #llm #anthropic #agentic-workflow #alignment </li>
<li>
<strong>Description:</strong> Research paper exploring robust AI agent design, presenting agentic workflow approaches, alignment methods, and techniques for autonomous, reliable tasks. </li>
</ul>
<h4>
Structured Outputs</h4>
<h5>
<a href="https://www.boundaryml.com/blog/structured-output-from-llms">Every Way To Get Structured Output From LLMs</a></h5>
<ul>
<li>
<strong>Type:</strong> 📄 Article 📚 </li>
<li>
<strong>Level:</strong> 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #structured-output #llm #function-calling #parsing #json </li>
<li>
<strong>Description:</strong> Provides various solutions for achieving structured output from LLMs when function calling or specific response formats become challenging. </li>
</ul>
<h4>
Vector Representations</h4>
<h5>
<a href="https://vickiboykis.com/what_are_embeddings/">What are Embeddings</a></h5>
<ul>
<li>
<strong>Type:</strong> 📄 Article 📚 </li>
<li>
<strong>Level:</strong> 🟢 Beginner to 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #embeddings #vector-representations #nlp #semantic-search </li>
<li>
<strong>Description:</strong> Comprehensive article exploring the concept of embeddings, their applications, and how they work in modern AI systems. </li>
</ul>
<h3>
AI Engineering</h3>
<h4>
Evaluation and Testing</h4>
<h5>
<a href="https://hamel.dev/blog/posts/evals/">Your AI Product Needs Evals</a></h5>
<ul>
<li>
<strong>Type:</strong> 📄 Article 📚 </li>
<li>
<strong>Level:</strong> 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #evaluation #ai-testing #product-development #quality-assessment </li>
<li>
<strong>Description:</strong> Structured, comprehensive resource on how to construct domain-specific evaluation systems for AI products. </li>
</ul>
<h4>
Data Pipelines</h4>
<h5>
<a href="https://www.sh-reya.com/blog/ai-engineering-flywheel/">Data Flywheels for LLM Applications</a></h5>
<ul>
<li>
<strong>Type:</strong> 📄 Article 📚 </li>
<li>
<strong>Level:</strong> 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #data-flywheel #llm #logging #evaluation #continuous-improvement </li>
<li>
<strong>Description:</strong> Breaks down how to improve AI systems iteratively through logging, evaluation, and continuous refinement processes. </li>
</ul>
<h4>
MLOps</h4>
<h5>
<a href="https://venturebeat.com/ai/mlops-vs-devops-why-data-makes-it-different/">MLOps vs. DevOps: Why data makes it different</a></h5>
<ul>
<li>
<strong>Type:</strong> 📄 Article </li>
<li>
<strong>Level:</strong> 🟢 Beginner </li>
<li>
<strong>Tags:</strong> #mlops #devops #data-centric #production-systems </li>
<li>
<strong>Description:</strong> Explains how machine learning operations differ from traditional DevOps due to ML’s direct exposure to messy real-world data. </li>
</ul>
<h3>
Data Science</h3>
<h4>
Data Analysis</h4>
<h5>
<a href="https://www.latent.space/p/2025-papers">The 2025 AI Engineer Reading List</a></h5>
<ul>
<li>
<strong>Type:</strong> 🔍 Research </li>
<li>
<strong>Level:</strong> 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #ai-engineering #papers #llm #benchmarks #prompting #rag #agents #code-generation </li>
<li>
<strong>Description:</strong> Curated list of 50 papers/models/blogs across 10 fields in AI Engineering, providing a solid foundation for understanding current research directions. </li>
</ul>
<h3>
Ethics and Responsible AI</h3>
<h4>
Perspectives from experts in this area include researchers focused on ethical AI development:</h4>
<h5>
<a href="https://bsky.app/profile/melaniemitchell.bsky.social">Melanie Mitchell</a></h5>
<ul>
<li>
<strong>Type:</strong> 👤 Person </li>
<li>
<strong>Level:</strong> 🟡 Intermediate to 🔴 Advanced </li>
<li>
<strong>Tags:</strong> #ai-ethics #complex-systems #computational-intelligence </li>
<li>
<strong>Description:</strong> Respected professor of computer science and prominent figure in complex systems and artificial intelligence, offering valuable perspectives on AI challenges. </li>
</ul>
<h3>
Technical Skills</h3>
<h4>
Presentations</h4>
<h5>
<a href="https://russelldavies.typepad.com/planning/2015/11/doing-presentations.html">Doing presentations</a></h5>
<ul>
<li>
<strong>Type:</strong> 📹 Talk </li>
<li>
<strong>Level:</strong> 🟢 Beginner </li>
<li>
<strong>Tags:</strong> #presentations #communication #slides #public-speaking </li>
<li>
<strong>Description:</strong> Collection of excellent presentations on how to present effectively. </li>
</ul>
<h5>
<a href="https://www.russelldavies.com/powerpoint">Everything I Know About Life I Learned From PowerPoint</a></h5>
<ul>
<li>
<strong>Type:</strong> 📕 Book 📚 </li>
<li>
<strong>Level:</strong> 🟢 Beginner </li>
<li>
<strong>Tags:</strong> #powerpoint #presentations #communication #visual-thinking </li>
<li>
<strong>Description:</strong> A book about PowerPoint built out of PowerPoint, covering communication techniques, culture, and effective presentation approaches. </li>
</ul>
<h4>
GPU Programming</h4>
<h5>
<a href="https://www.youtube.com/channel/UCJgIbYl6C5no72a0NUAPcTA">GPU MODE</a></h5>
<ul>
<li>
<strong>Type:</strong> 📹 Talk </li>
<li>
<strong>Level:</strong> 🟡 Intermediate to 🔴 Advanced </li>
<li>
<strong>Tags:</strong> #gpu-programming #cuda #flash-attention #triton #quantisation </li>
<li>
<strong>Description:</strong> Channel with excellent material on GPU programming, including CUDA kernels, Flash Attention, Triton, and quantisation techniques. </li>
</ul>
<h2>
By Format</h2>
<h3>
Books</h3>
<h4>
<a href="https://ml-science-book.com/">Supervised Machine Learning for Science</a></h4>
<ul>
<li>
<strong>Type:</strong> 📕 Book 📚 </li>
<li>
<strong>Level:</strong> 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #machine-learning #supervised-learning #science #best-practices </li>
<li>
<strong>Description:</strong> Explores the role of supervised machine learning in scientific research with philosophical justifications and integration best practices. </li>
</ul>
<h4>
<a href="https://cs.gmu.edu/~sean/book/metaheuristics/">Essentials of Metaheuristics</a></h4>
<ul>
<li>
<strong>Type:</strong> 📕 Book 📚 </li>
<li>
<strong>Level:</strong> 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #algorithms #optimisation #metaheuristics #stochastic </li>
<li>
<strong>Description:</strong> Open lecture notes on metaheuristic algorithms, covering stochastic optimisation methods intended as alternatives to brute-force search. </li>
</ul>
<h4>
<a href="https://leanpub.com/ollama">Ollama in Action</a></h4>
<ul>
<li>
<strong>Type:</strong> 📕 Book 📚 </li>
<li>
<strong>Level:</strong> 🟢 Beginner to 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #llm #ollama #on-premise #privacy #function-calling #agents </li>
<li>
<strong>Description:</strong> Demonstrates how to run LLMs on-premise to maintain data privacy and control of your tech stack, with clear Python code examples. </li>
</ul>
<h4>
<a href="https://ravinkumar.com/GenAiGuidebook/book_intro.html">The GenAI Guidebook</a></h4>
<ul>
<li>
<strong>Type:</strong> 📕 Book 📚 </li>
<li>
<strong>Level:</strong> 🟢 Beginner to 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #genai #product-development #foundation-models #implementation </li>
<li>
<strong>Description:</strong> Comprehensive guide laying out the foundations for building products with Generative AI. </li>
</ul>
<h4>
<a href="https://www.russelldavies.com/powerpoint">Everything I Know About Life I Learned From PowerPoint</a></h4>
<ul>
<li>
<strong>Type:</strong> 📕 Book 📚 </li>
<li>
<strong>Level:</strong> 🟢 Beginner </li>
<li>
<strong>Tags:</strong> #powerpoint #presentations #communication #visual-thinking </li>
<li>
<strong>Description:</strong> A book about PowerPoint built out of PowerPoint, covering communication techniques, culture, and effective presentation approaches. </li>
</ul>
<h3>
Courses</h3>
<h4>
<a href="https://course.fast.ai/">Fast.ai’s Practical Deep Learning</a></h4>
<ul>
<li>
<strong>Type:</strong> 🎓 Course 📚 </li>
<li>
<strong>Level:</strong> 🟢 Beginner to 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #deep-learning #practical #hands-on #fastai </li>
<li>
<strong>Description:</strong> A rich, practice-oriented course that teaches how to apply deep learning to practical problems, complemented by the <a href="https://github.com/fastai/fastbook">Fastbook</a>. </li>
</ul>
<h4>
<a href="https://xcancel.com/hugobowne/status/1870978490574704812">Building LLM Applications</a></h4>
<ul>
<li>
<strong>Type:</strong> 🎓 Course 📚 </li>
<li>
<strong>Level:</strong> 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #llm #software-development #agents #evaluation #best-practices </li>
<li>
<strong>Description:</strong> Teaches how to build LLM-powered software reliably, from first principles, covering the entire GenAI software development lifecycle. </li>
</ul>
<h4>
<a href="https://rdi.berkeley.edu/llm-agents/f24">CS294/194-196 Large Language Model Agents</a></h4>
<ul>
<li>
<strong>Type:</strong> 🎓 Course 📚 </li>
<li>
<strong>Level:</strong> 🟡 Intermediate to 🔴 Advanced </li>
<li>
<strong>Tags:</strong> #llm #agents #foundation-models #task-automation </li>
<li>
<strong>Description:</strong> Comprehensive course discussing fundamental concepts for LLM agents, including LLM foundations, essential abilities for task automation, and agent development infrastructure. </li>
</ul>
<h3>
Articles</h3>
<h4>
<a href="https://hamel.dev/blog/posts/evals/">Your AI Product Needs Evals</a></h4>
<ul>
<li>
<strong>Type:</strong> 📄 Article 📚 </li>
<li>
<strong>Level:</strong> 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #evaluation #ai-testing #product-development #quality-assessment </li>
<li>
<strong>Description:</strong> Structured, comprehensive resource on how to construct domain-specific evaluation systems for AI products. </li>
</ul>
<h4>
<a href="https://www.sh-reya.com/blog/ai-engineering-flywheel/">Data Flywheels for LLM Applications</a></h4>
<ul>
<li>
<strong>Type:</strong> 📄 Article 📚 </li>
<li>
<strong>Level:</strong> 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #data-flywheel #llm #logging #evaluation #continuous-improvement </li>
<li>
<strong>Description:</strong> Breaks down how to improve AI systems iteratively through logging, evaluation, and continuous refinement processes. </li>
</ul>
<h4>
<a href="https://applied-llms.org/">What We’ve Learned From A Year of Building with LLMs</a></h4>
<ul>
<li>
<strong>Type:</strong> 📄 Article 📚 </li>
<li>
<strong>Level:</strong> 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #llm #product-development #lessons-learned #applied-ai </li>
<li>
<strong>Description:</strong> Practical guide to building successful LLM products, covering tactical, operational, and strategic considerations, complemented by podcast episodes <a href="https://vanishinggradients.fireside.fm/29">29</a> and <a href="https://vanishinggradients.fireside.fm/30">30</a>. </li>
</ul>
<h4>
<a href="https://www.anthropic.com/engineering/building-effective-agents">Building Effective Agents</a></h4>
<ul>
<li>
<strong>Type:</strong> 📄 Article 📚 </li>
<li>
<strong>Level:</strong> 🟡 Intermediate to 🔴 Advanced </li>
<li>
<strong>Tags:</strong> #agents #llm #anthropic #agentic-workflow #alignment </li>
<li>
<strong>Description:</strong> Research paper exploring robust AI agent design, presenting agentic workflow approaches, alignment methods, and techniques for autonomous, reliable tasks. </li>
</ul>
<h4>
<a href="https://vickiboykis.com/what_are_embeddings/">What are Embeddings</a></h4>
<ul>
<li>
<strong>Type:</strong> 📄 Article 📚 </li>
<li>
<strong>Level:</strong> 🟢 Beginner to 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #embeddings #vector-representations #nlp #semantic-search </li>
<li>
<strong>Description:</strong> Comprehensive article exploring the concept of embeddings, their applications, and how they work in modern AI systems. </li>
</ul>
<h4>
<a href="https://www.boundaryml.com/blog/structured-output-from-llms">Every Way To Get Structured Output From LLMs</a></h4>
<ul>
<li>
<strong>Type:</strong> 📄 Article 📚 </li>
<li>
<strong>Level:</strong> 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #structured-output #llm #function-calling #parsing #json </li>
<li>
<strong>Description:</strong> Provides various solutions for achieving structured output from LLMs when function calling or specific response formats become challenging. </li>
</ul>
<h4>
<a href="https://venturebeat.com/ai/mlops-vs-devops-why-data-makes-it-different/">MLOps vs. DevOps: Why data makes it different</a></h4>
<ul>
<li>
<strong>Type:</strong> 📄 Article </li>
<li>
<strong>Level:</strong> 🟢 Beginner </li>
<li>
<strong>Tags:</strong> #mlops #devops #data-centric #production-systems </li>
<li>
<strong>Description:</strong> Explains how machine learning operations differ from traditional DevOps due to ML’s direct exposure to messy real-world data. </li>
</ul>
<h3>
Talks and Presentations</h3>
<h4>
<a href="https://russelldavies.typepad.com/planning/2015/11/doing-presentations.html">Doing presentations</a></h4>
<ul>
<li>
<strong>Type:</strong> 📹 Talk </li>
<li>
<strong>Level:</strong> 🟢 Beginner </li>
<li>
<strong>Tags:</strong> #presentations #communication #slides #public-speaking </li>
<li>
<strong>Description:</strong> Collection of excellent presentations on how to present effectively. </li>
</ul>
<h4>
<a href="https://dotclub.club/">The .CLUB Club</a></h4>
<ul>
<li>
<strong>Type:</strong> 📹 Talk </li>
<li>
<strong>Level:</strong> 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #engineering-leadership #tech-solutions #workplace-politics #egoless-engineering </li>
<li>
<strong>Description:</strong> Insightful talks on egoless engineering, straightforward tech solutions, and workplace politics from an engineering leadership perspective. </li>
</ul>
<h4>
<a href="https://media.ccc.de/">ccc.de</a></h4>
<ul>
<li>
<strong>Type:</strong> 📹 Talk </li>
<li>
<strong>Level:</strong> 🟡 Intermediate to 🔴 Advanced </li>
<li>
<strong>Tags:</strong> #hacking #reverse-engineering #security #technical-exploration </li>
<li>
<strong>Description:</strong> Vast collection of presentations by the Chaos Computer Club, covering reverse engineering, cutting-edge exploration, and authentic engineering concepts. </li>
</ul>
<h4>
<a href="https://www.youtube.com/channel/UCJgIbYl6C5no72a0NUAPcTA">GPU MODE</a></h4>
<ul>
<li>
<strong>Type:</strong> 📹 Talk </li>
<li>
<strong>Level:</strong> 🟡 Intermediate to 🔴 Advanced </li>
<li>
<strong>Tags:</strong> #gpu-programming #cuda #flash-attention #triton #quantisation </li>
<li>
<strong>Description:</strong> Channel with excellent material on GPU programming, including CUDA kernels, Flash Attention, Triton, and quantisation techniques. </li>
</ul>
<h3>
Newsletters</h3>
<h4>
<a href="https://buttondown.com/ainews/archive/">AI News</a></h4>
<ul>
<li>
<strong>Type:</strong> 📰 Newsletter </li>
<li>
<strong>Level:</strong> 🟢 Beginner to 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #ai-news #trends #research #development </li>
<li>
<strong>Description:</strong> Daily newsletter summarising top discussions in AI-focused online communities, covering latest trends, research, and developments. </li>
</ul>
<h4>
<a href="https://aibyhand.substack.com/">AI by Hand</a></h4>
<ul>
<li>
<strong>Type:</strong> 📰 Newsletter </li>
<li>
<strong>Level:</strong> 🟢 Beginner </li>
<li>
<strong>Tags:</strong> #ai-education #machine-learning #accessible-explanations </li>
<li>
<strong>Description:</strong> Newsletter by Professor Tom Yeh providing insights and educational content with accessible explanations of AI concepts. </li>
</ul>
<h3>
Research Resources</h3>
<h4>
<a href="https://www.emergentmind.com/">Emergent Mind</a></h4>
<ul>
<li>
<strong>Type:</strong> 🔍 Research </li>
<li>
<strong>Level:</strong> 🟡 Intermediate to 🔴 Advanced </li>
<li>
<strong>Tags:</strong> #research-assistant #arxiv #computer-science #trending-papers </li>
<li>
<strong>Description:</strong> AI research assistant that synthesises the latest computer science research from arXiv and surfaces trending pre-prints. </li>
</ul>
<h4>
<a href="https://www.latent.space/p/2025-papers">The 2025 AI Engineer Reading List</a></h4>
<ul>
<li>
<strong>Type:</strong> 🔍 Research </li>
<li>
<strong>Level:</strong> 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #ai-engineering #papers #llm #benchmarks #prompting #rag #agents #code-generation </li>
<li>
<strong>Description:</strong> Curated list of 50 papers/models/blogs across 10 fields in AI Engineering, providing a solid foundation for understanding current research directions. </li>
</ul>
<h4>
<a href="https://ourworldindata.org/">Our World in Data</a></h4>
<ul>
<li>
<strong>Type:</strong> 🔍 Research </li>
<li>
<strong>Level:</strong> 🟢 Beginner to 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #data-visualisation #global-issues #research #evidence-based </li>
<li>
<strong>Description:</strong> Project from the University of Oxford providing data-driven insights into global issues, valuable for understanding the world’s largest problems and potential solutions. </li>
</ul>
<h3>
Social Media</h3>
<h4>
<a href="https://bsky.app/profile/erictopol.bsky.social">Eric Topol</a></h4>
<ul>
<li>
<strong>Type:</strong> 👤 Person </li>
<li>
<strong>Level:</strong> 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #healthcare #medical-ai #future-medicine #technology </li>
<li>
<strong>Description:</strong> Renowned cardiologist, scientist, and author who has written extensively on the future of medicine, including AI and digital technologies impact. </li>
</ul>
<h4>
<a href="https://bsky.app/profile/howard.fm">Jeremy Howard</a></h4>
<ul>
<li>
<strong>Type:</strong> 👤 Person </li>
<li>
<strong>Level:</strong> 🟡 Intermediate to 🔴 Advanced </li>
<li>
<strong>Tags:</strong> #data-science #fastai #deep-learning #ai-education </li>
<li>
<strong>Description:</strong> Prominent data scientist, co-founder of fast.ai and answer.ai, providing educational content and research insights in data science. </li>
</ul>
<h4>
<a href="https://bsky.app/profile/math-rachel.bsky.social">Rachel Thomas</a></h4>
<ul>
<li>
<strong>Type:</strong> 👤 Person </li>
<li>
<strong>Level:</strong> 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #data-science #ai-ethics #ai-education #mathematics </li>
<li>
<strong>Description:</strong> 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. </li>
</ul>
<h4>
<a href="https://xcancel.com/karpathy">Andrej Karpathy</a></h4>
<ul>
<li>
<strong>Type:</strong> 👤 Person </li>
<li>
<strong>Level:</strong> 🟡 Intermediate to 🔴 Advanced </li>
<li>
<strong>Tags:</strong> #ai-research #deep-learning #tesla #openai </li>
<li>
<strong>Description:</strong> Leading AI researcher and educator, former Director of AI at Tesla and founding team member at OpenAI, providing in-depth insights on AI advancements. </li>
</ul>
<h4>
<a href="https://bsky.app/profile/simonwillison.net">Simon Willison</a></h4>
<ul>
<li>
<strong>Type:</strong> 👤 Person </li>
<li>
<strong>Level:</strong> 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #open-source #datasette #django #data-tools </li>
<li>
<strong>Description:</strong> Independent open-source developer and data leader, creator of Datasette and co-creator of Django, with significant contributions to open-source community. </li>
</ul>
<h4>
<a href="https://bsky.app/profile/melaniemitchell.bsky.social">Melanie Mitchell</a></h4>
<ul>
<li>
<strong>Type:</strong> 👤 Person </li>
<li>
<strong>Level:</strong> 🟡 Intermediate to 🔴 Advanced </li>
<li>
<strong>Tags:</strong> #ai-ethics #complex-systems #computational-intelligence </li>
<li>
<strong>Description:</strong> Respected professor of computer science and prominent figure in complex systems and artificial intelligence, offering valuable perspectives on AI challenges. </li>
</ul>
<h4>
<a href="https://bsky.app/profile/maosbot.bsky.social/post/3laix6hz42n2m">Michael A. Osborne</a></h4>
<ul>
<li>
<strong>Type:</strong> 👤 Person </li>
<li>
<strong>Level:</strong> 🔴 Advanced </li>
<li>
<strong>Tags:</strong> #machine-learning #bayesian-optimisation #battery-modeling #quantum-devices </li>
<li>
<strong>Description:</strong> Professor of machine learning focused on Bayesian optimisation and applications in battery modeling and quantum devices, creator of Bluesky starter packs for prominent figures. </li>
</ul>
<h4>
<a href="https://bsky.app/profile/christophmolnar.bsky.social">Christoph Molnar</a></h4>
<ul>
<li>
<strong>Type:</strong> 👤 Person </li>
<li>
<strong>Level:</strong> 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #statistics #ml-interpretability #uncertainty-quantification #mindful-modeler </li>
<li>
<strong>Description:</strong> Statistician and ML expert specialising in interpretability and uncertainty quantification, author of books on interpretable ML and modeling mindsets. </li>
</ul>
<h2>
By Expertise Level</h2>
<h3>
Beginner</h3>
<h4>
<a href="https://russelldavies.typepad.com/planning/2015/11/doing-presentations.html">Doing presentations</a></h4>
<ul>
<li>
<strong>Type:</strong> 📹 Talk </li>
<li>
<strong>Level:</strong> 🟢 Beginner </li>
<li>
<strong>Tags:</strong> #presentations #communication #slides #public-speaking </li>
<li>
<strong>Description:</strong> Collection of excellent presentations on how to present effectively. </li>
</ul>
<h4>
<a href="https://www.russelldavies.com/powerpoint">Everything I Know About Life I Learned From PowerPoint</a></h4>
<ul>
<li>
<strong>Type:</strong> 📕 Book 📚 </li>
<li>
<strong>Level:</strong> 🟢 Beginner </li>
<li>
<strong>Tags:</strong> #powerpoint #presentations #communication #visual-thinking </li>
<li>
<strong>Description:</strong> A book about PowerPoint built out of PowerPoint, covering communication techniques, culture, and effective presentation approaches. </li>
</ul>
<h4>
<a href="https://venturebeat.com/ai/mlops-vs-devops-why-data-makes-it-different/">MLOps vs. DevOps: Why data makes it different</a></h4>
<ul>
<li>
<strong>Type:</strong> 📄 Article </li>
<li>
<strong>Level:</strong> 🟢 Beginner </li>
<li>
<strong>Tags:</strong> #mlops #devops #data-centric #production-systems </li>
<li>
<strong>Description:</strong> Explains how machine learning operations differ from traditional DevOps due to ML’s direct exposure to messy real-world data. </li>
</ul>
<h4>
<a href="https://aibyhand.substack.com/">AI by Hand</a></h4>
<ul>
<li>
<strong>Type:</strong> 📰 Newsletter </li>
<li>
<strong>Level:</strong> 🟢 Beginner </li>
<li>
<strong>Tags:</strong> #ai-education #machine-learning #accessible-explanations </li>
<li>
<strong>Description:</strong> Newsletter by Professor Tom Yeh providing insights and educational content with accessible explanations of AI concepts. </li>
</ul>
<h3>
Intermediate</h3>
<h4>
<a href="https://ml-science-book.com/">Supervised Machine Learning for Science</a></h4>
<ul>
<li>
<strong>Type:</strong> 📕 Book 📚 </li>
<li>
<strong>Level:</strong> 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #machine-learning #supervised-learning #science #best-practices </li>
<li>
<strong>Description:</strong> Explores the role of supervised machine learning in scientific research with philosophical justifications and integration best practices. </li>
</ul>
<h4>
<a href="https://xcancel.com/hugobowne/status/1870978490574704812">Building LLM Applications</a></h4>
<ul>
<li>
<strong>Type:</strong> 🎓 Course 📚 </li>
<li>
<strong>Level:</strong> 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #llm #software-development #agents #evaluation #best-practices </li>
<li>
<strong>Description:</strong> Teaches how to build LLM-powered software reliably, from first principles, covering the entire GenAI software development lifecycle. </li>
</ul>
<h4>
<a href="https://hamel.dev/blog/posts/evals/">Your AI Product Needs Evals</a></h4>
<ul>
<li>
<strong>Type:</strong> 📄 Article 📚 </li>
<li>
<strong>Level:</strong> 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #evaluation #ai-testing #product-development #quality-assessment </li>
<li>
<strong>Description:</strong> Structured, comprehensive resource on how to construct domain-specific evaluation systems for AI products. </li>
</ul>
<h4>
<a href="https://dotclub.club/">The .CLUB Club</a></h4>
<ul>
<li>
<strong>Type:</strong> 📹 Talk </li>
<li>
<strong>Level:</strong> 🟡 Intermediate </li>
<li>
<strong>Tags:</strong> #engineering-leadership #tech-solutions #workplace-politics #egoless-engineering </li>
<li>
<strong>Description:</strong> Insightful talks on egoless engineering, straightforward tech solutions, and workplace politics from an engineering leadership perspective. </li>
</ul>
<h3>
Advanced</h3>
<h4>
<a href="https://rdi.berkeley.edu/llm-agents/f24">CS294/194-196 Large Language Model Agents</a></h4>
<ul>
<li>
<strong>Type:</strong> 🎓 Course 📚 </li>
<li>
<strong>Level:</strong> 🟡 Intermediate to 🔴 Advanced </li>
<li>
<strong>Tags:</strong> #llm #agents #foundation-models #task-automation </li>
<li>
<strong>Description:</strong> Comprehensive course discussing fundamental concepts for LLM agents, including LLM foundations, essential abilities for task automation, and agent development infrastructure. </li>
</ul>
<h4>
<a href="https://www.anthropic.com/engineering/building-effective-agents">Building Effective Agents</a></h4>
<ul>
<li>
<strong>Type:</strong> 📄 Article 📚 </li>
<li>
<strong>Level:</strong> 🟡 Intermediate to 🔴 Advanced </li>
<li>
<strong>Tags:</strong> #agents #llm #anthropic #agentic-workflow #alignment </li>
<li>
<strong>Description:</strong> Research paper exploring robust AI agent design, presenting agentic workflow approaches, alignment methods, and techniques for autonomous, reliable tasks. </li>
</ul>
<h4>
<a href="https://www.youtube.com/channel/UCJgIbYl6C5no72a0NUAPcTA">GPU MODE</a></h4>
<ul>
<li>
<strong>Type:</strong> 📹 Talk </li>
<li>
<strong>Level:</strong> 🟡 Intermediate to 🔴 Advanced </li>
<li>
<strong>Tags:</strong> #gpu-programming #cuda #flash-attention #triton #quantisation </li>
<li>
<strong>Description:</strong> Channel with excellent material on GPU programming, including CUDA kernels, Flash Attention, Triton, and quantisation techniques. </li>
</ul>
<h4>
<a href="https://bsky.app/profile/maosbot.bsky.social/post/3laix6hz42n2m">Michael A. Osborne</a></h4>
<ul>
<li>
<strong>Type:</strong> 👤 Person </li>
<li>
<strong>Level:</strong> 🔴 Advanced </li>
<li>
<strong>Tags:</strong> #machine-learning #bayesian-optimisation #battery-modeling #quantum-devices </li>
<li>
<strong>Description:</strong> Professor of machine learning focused on Bayesian optimisation and applications in battery modeling and quantum devices, creator of Bluesky starter packs for prominent figures. </li>
</ul>
<h2>
Tag Index</h2>
<ul>
<li>
<strong>#accessible-explanations</strong>: <a href="#ai-by-hand">AI by Hand</a> </li>
<li>
<strong>#agents</strong>: <a href="#building-llm-applications">Building LLM Applications</a>, <a href="#cs294194-196-large-language-model-agents">CS294/194-196 Large Language Model Agents</a>, <a href="#building-effective-agents">Building Effective Agents</a>, <a href="#ollama-in-action">Ollama in Action</a>, <a href="#the-2025-ai-engineer-reading-list">The 2025 AI Engineer Reading List</a> </li>
<li>
<strong>#ai-education</strong>: <a href="#ai-by-hand">AI by Hand</a>, <a href="#rachel-thomas">Rachel Thomas</a> </li>
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<strong>#ai-engineering</strong>: <a href="#the-2025-ai-engineer-reading-list">The 2025 AI Engineer Reading List</a> </li>
<li>
<strong>#ai-ethics</strong>: <a href="#rachel-thomas">Rachel Thomas</a>, <a href="#melanie-mitchell">Melanie Mitchell</a> </li>
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<strong>#ai-news</strong>: <a href="#ai-news">AI News</a> </li>
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<strong>#ai-research</strong>: <a href="#andrej-karpathy">Andrej Karpathy</a> </li>
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<strong>#ai-testing</strong>: <a href="#your-ai-product-needs-evals">Your AI Product Needs Evals</a> </li>
<li>
<strong>#algorithms</strong>: <a href="#essentials-of-metaheuristics">Essentials of Metaheuristics</a> </li>
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<strong>#alignment</strong>: <a href="#building-effective-agents">Building Effective Agents</a> </li>
<li>
<strong>#anthropic</strong>: <a href="#building-effective-agents">Building Effective Agents</a> </li>
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<strong>#agentic-workflow</strong>: <a href="#building-effective-agents">Building Effective Agents</a> </li>
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<strong>#applied-ai</strong>: <a href="#what-weve-learned-from-a-year-of-building-with-llms">What We’ve Learned From A Year of Building with LLMs</a> </li>
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<strong>#arxiv</strong>: <a href="#emergent-mind">Emergent Mind</a> </li>
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<strong>#bayesian-optimisation</strong>: <a href="#michael-a-osborne">Michael A. Osborne</a> </li>
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<strong>#battery-modeling</strong>: <a href="#michael-a-osborne">Michael A. Osborne</a> </li>
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<strong>#benchmarks</strong>: <a href="#the-2025-ai-engineer-reading-list">The 2025 AI Engineer Reading List</a> </li>
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<strong>#best-practices</strong>: <a href="#supervised-machine-learning-for-science">Supervised Machine Learning for Science</a>, <a href="#building-llm-applications">Building LLM Applications</a> </li>
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<strong>#code-generation</strong>: <a href="#the-2025-ai-engineer-reading-list">The 2025 AI Engineer Reading List</a> </li>
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<strong>#communication</strong>: <a href="#doing-presentations">Doing presentations</a>, <a href="#everything-i-know-about-life-i-learned-from-powerpoint">Everything I Know About Life I Learned From PowerPoint</a> </li>
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<strong>#complex-systems</strong>: <a href="#melanie-mitchell">Melanie Mitchell</a> </li>
<li>
<strong>#computational-intelligence</strong>: <a href="#melanie-mitchell">Melanie Mitchell</a> </li>
<li>
<strong>#computer-science</strong>: <a href="#emergent-mind">Emergent Mind</a> </li>
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<strong>#continuous-improvement</strong>: <a href="#data-flywheels-for-llm-applications">Data Flywheels for LLM Applications</a> </li>
<li>