Forewords

This is the 3rd time updating the lists, where I added a section of Prompt Engineering upon requests since it is a good starting point for those not into self-hosting nor theory. The term “Prompt Engineering” is a bit controversial but people will get better understanding after learning the listed materials.

As a lifelong self-learner, I use all sorts of methods to learn new things, and AI is what I’m currently into. Although I’ve been using AI tools since 2022, my background wasn’t focused on AI. So, like everyone else, I had to do some “AI For Dummies” level study in order to get more involved. Below is a list of learning materials that I find very helpful for myself to get started with and might also be helpful for someone else in the same situation.

Overview

1. Large Language Models Explained Briefly

  • Type: Video
  • Note: Created by the popular channel 3Blue1Brown, this video uses intuitive visuals and simple language to explain how large language models (LLMs) work. Perfect for beginners who want a quick, accessible understanding of LLMs without diving into technical details.

2. Large Language Models: A Survey

  • Type: Research paper

  • Note: This survey provides a high-level summary of LLM developments, making it ideal for curious learners interested in understanding the evolution and variety of these models without getting overwhelmed by book.

  1. A Comprehensive Overview of Large Language Models

  • Type: Research paper

  • Note: Provides an in-depth examination of LLM architecture, training strategies, and multimodal applications. Essential for researchers and advanced practitioners seeking detailed insights into the state-of-the-art in LLMs.

4. 2024 AI Index Report

  • Type: Comprehensive report
  • Note: This annual report from Stanford offers insights into the latest AI trends, including research, ethics, and global adoption. A must-read for policymakers, educators, and tech enthusiasts seeking a broad overview of AI’s impact.

5. Generative AI Overview

  • Type: Web article

  • Note: Gartner’s accessible yet detailed coverage is perfect for business professionals and anyone interested in how generative AI can be applied across industries.

6. A Survey of Large Language Models

  • Type: Bookish paper
  • Note: Dubbed more of a book than a research paper, this resource dives deep into the technical architecture and methodologies of LLMs. Best suited for researchers and advanced learners. Chapter 6 UTILIZATION introduces some hands-on techniques on prompting.

Prompt Engineering

1. Master Prompt Engineering for Beginners

  • Type: Video
  • Note: Created by AI Foundations, this compact video covers the fundamental skills of learning/using AI chatbot. Before building cool things like agents and automations, or even learn more theories, the basics must not being skipped.

2. Learn Prompt Engineering: Full Beginner Crash Course

  • Type: Video
  • Note: Created by Zero To Mastery, this 5 hours long crash course covers all the details for beginners to learn and master the fundamentals of Prompt Engineering and how to use LLMs. Instead of memorizing random prompt templates, learning how LLMs actually work under the hood is the right appoarch to use them effectively in various use cases.

3. DAIR.AI’s Guide

  • Type: Webpage
  • Note: This free and open-source guide covers the theory and practical aspects of prompt engineering and how to leverage the best prompting techniques to interact and build with LLMs.

4. Learn Prompting’s Guide

  • Type: Webpage
  • Note: This free and open-source course is tailored to non-technical readers, who may not have even heard of AI, making it the perfect starting point if you are new to Generative AI and Prompt Engineering.

Theory

1. Artificial Intelligence: A Guide for Thinking Humans

2. Hands-On Large Language Models

  • Type: Book
  • Note: This practical guide teaches you how to build, fine-tune, and deploy LLMs. Ideal for developers, data scientists, and AI practitioners ready to get their hands dirty. Also available on shadow libraries. Chapter 6 Prompt Engineering shows some basic techniques to construct a good prompt.

3. The 2025 AI Engineer Reading List

  • Type: Reading list
  • Note: By the popular podcast show Latent Space. A goldmine for aspiring AI engineers, this list highlights the most influential papers, books, and resources to stay ahead in AI development for this year.

4. Generative AI Handbook

  • Type: Reading list
  • Note: Offers a roadmap to mastering generative AI, from fundamentals to advanced topics. Great for learners who value organized study paths.

5. Ahead of AI Magazine

  • Type: Digital magazine
  • Note: Authored by AI expert Sebastian Raschka, this magazine covers technical and philosophical discussions about AI. Ideal for anyone interested in both the practical and theoretical aspects of the field.

6. Awesome List of Cybersecurity and AI

  • Type: Reading list
  • Note: This curated list focuses on the intersection of AI and cybersecurity, making it invaluable for security professionals and researchers.

7. Complexity and the Economy

  • Type: Book
  • Note: This work examines the role of complexity in economic systems, offering insights into how economies evolve and adapt, relevant for understanding the broader context of AI’s impact.

Blogs

1. Simon Willison’s Weblog

  • Note: Simon’s posts trending news and technical details with accessible narratives, catering to open-source developers and AI enthusiasts.

2. AI, Software, Tech, and People by X

  • Note: Xavier Amatriain’s blog offers insightful commentary on AI’s impact on society, making it a thoughtful read for non-technical audiences.

3. The Kaitchup – AI on a Budget

  • Note: Benjamin Marie’s posts The Weekly Kaitchup news and running open LLMs locally, ideal for small businesses, startups, and hobbyists.

4. Center for Democracy and Technology

  • Note: CDT is advocating the policy, regulation, and governance of AI, to ensure AI develops in a manner that is consistent with human rights and democratic values.

Podcasts

1. Around the Prompt

  • Note: Delving into AI innovation with leading experts, uncovers untapped potential and provides practical insights for enthusiasts and newcomers alike.

2. The Gradient

  • Note: Provides diverse perspectives on AI from researchers, builders, and users across academia, engineering, art, and entrepreneurship, making it ideal for a broad audience seeking multifaceted insights.

3. Practical AI

  • Note: By Changelog Media, makes artificial intelligence practical, productive, and accessible to everyone.

4. The TWIML AI Podcast

  • Note: Sam Charrington’s discussions with top industry experts on cutting-edge machine learning and AI technologies, providing valuable knowledge for researchers, engineers, and tech leaders.

5. Unsupervised Learning

  • Note: By AI / Security Researcher and Entrepreneur, Daniel Miessler. Unsupervised Learning is a website, newsletter, and podcast about how to survive and thrive as humans in a post-AI world.

6. The Cognitive Revolution

  • Note: A weekly podcast where host Nathan Labenz interviews AI innovators, diving into the transformative impact AI will have in the near future.

7. Latent Space Podcast

  • Note: Top 10 US Tech podcast. Exploring AI UX, Agents, Devtools, Infra, Open Source Models for AI Engineers.

Afterwords

Keep practicing while learning theory is the best way to go—using AI on current device via self-hosting local LLMs, or a step further by building a homebrew AI Lab. Nowadays, we have tools such as Ollama, jan and llamafile, which provide user friendly, easy deployment and better privacy.