10 Best Resources to Learn AI and LLM Engineering in 2025

The only roadmap you need to go from Developer to AI Engineer

10 Best Resources to Learn AI and LLM Engineering
credit — Paul Iustzin, author LLM ENgineering HandBook

Hello guys, Artificial Intelligence is no longer optional for developers — it’s essential. While there are people who are worried about AI taking jobs then there are also people are cashing on this unique opportunity of AI engineering.

This post is about second group of people who want to learn and excel in this AI era.

Whether you’re a backend developer, frontend engineer, or DevOps pro, understanding how to build, deploy, and reason about Large Language Models (LLMs) is quickly becoming the skill that separates good developers from great ones.

The best part? You don’t need a PhD or formal ML degree to get started. Thanks to the rise of excellent books and project-based online courses, you can become proficient in AI and LLM engineering with the right resources.

In the past, I have shared AI and LLM Engineering RoadMap and best AI books and courses and In this post, I’m sharing 10 of the most recommended books and courses to help you master AI Engineering in 2025 — handpicked from my research and personal learning path.

So, what are we waiting for, let’s dive in ..

10 Best AI and LLM Engineering Resources for Software Engineers in 2025

Without any further ado, here are the best resources you can get to learn about AI and LLM Engineering in depth and become an AI Engineer in 2025.

This include both books and courses which you can read and join online to start with. I am also planning to add projects, GitHub repository and some YouTube channels later, but if you have got any suggestion, feel free to drop a note on comments.

1. AI Engineering by Chip Huyen (Book)

This is the book you may have seen recommended all over the place, from Reddit to Twitter, and from HN to Facebook, and why not?

This is a definitive guide to understanding the real-world engineering challenges of building AI systems — from MLOps to real-time inference to data-centric AI.

Chip Huyen brings her experience from Stanford and Claypot AI to help you think like an AI engineer. You will learn all the skills you need to transition from Software Engineer to AI Engineer in this book.

If you can read just one book then you must read this one and that’s why I have put this book at the top.

Perfect for: Backend and software engineers transitioning into AI roles.

Here is the link to get the book — AI Engineering by Chip Huyen

2. The AI Engineer Course 2025: Complete AI Engineer Bootcamp (Udemy)

I normally combine books with courses to get both active and passive learning. When I get bored of reading books, I watch courses and when I get bored of courses, I start building projects.

This is one of the most comprehensive bootcamps for building GenAI, RAG, LLM agents, and deploying LLM-based apps. Taught with practical projects using LangChain, Vector DBs, and fine-tuning.

Perfect for: Hands-on learners who want to build AI-powered apps.

Here is the link to join this course — The AI Engineer Course 2025: Complete AI Engineer Bootcamp

3. The LLM Engineering Handbook by Paul Iusztin and Maxime Labonne (Book)

This is another book which I highly recommend to Software Engineer who wants to deep dive into LLM Engineering.

Created by Paul Iustzin and Maxime Labonne, this handbook explains how to structure and deploy real LLM apps — covering vector search, prompt chaining, evals, LangChain, OpenAI, and RAG.

Apart from AI Engineering the previous book, I highly recommend this book to anyone who wants to learn about LLM in depth.

Perfect for: Devs looking to go deeper than just calling GPT APIs.

Here is the link to get this book — The LLM Engineering Handbook

4. LLM Engineering: Master AI, Large Language Models & Agents (Udemy)

This LLM engineering course on Udemy covers everything from building RAG pipelines to AI agents and multi-modal applications.

This is also a project-based course and ideal for developers transitioning from traditional software to GenAI.

Perfect for: Developers looking to build production-ready LLM projects.

Here is the link to join this course — LLM Engineering: Master AI, Large Language Models & Agents

5. Designing Machine Learning Systems by Chip Huyen (Book)

This is another great resource for AI Engineers from Chip Huyen which focuses on designing scalable ML pipelines — bridging the gap between software engineering and ML.

This book also covers deployment, monitoring, testing, and architecture.

Perfect for: AI engineers looking to build robust ML systems, not just models.

Get the book →

6. Generative AI for Everyone by Andrew Ng (Coursera)

Couersra has a lot of great resources to learn AI and LLM Engineering which is created by top notch engineers and educated.

One of those course is Generative AI for Everyone where Andrew Ng demystifies GenAI for beginners.

This course explains how tools like ChatGPT, Stable Diffusion, and others work under the hood and how they’re changing industries.

Perfect for: Beginners and business-savvy engineers.

Here is the link to join this course — Generative AI for Everyone

By the way, If you are planning to join multiple specializations, then consider taking a Coursera Plus subscription which provides you unlimited access to their most popular courses, specialization, professional certificate, and guided projects.

7. Build a Large Language Model (from Scratch) by Sebastian Raschka, PhD (Book)

Want to understand what makes GPT-3 tick? This book teaches you how to build transformer models from scratch in PyTorch. A masterclass in deep learning mechanics.

Perfect for: Advanced engineers who want to go beyond API usage.

Get the book →

8. Spring AI: Build LLM Apps with Java and Spring Boot (Udemy)

This is another practical AI course for Java developers from Udemy.

This course teaches how to integrate OpenAI, Ollama, and RAG into Java-based Spring Boot apps using Spring AI — perfect for enterprise Java developers stepping into AI.

Perfect for: Java developers looking to build LLM-powered applications.

Here is the link to join this course — Spring AI: Build LLM Apps with Java and Spring Boot

9. Prompt Engineering for LLMs (Book)

Prompting is a real skill, and this book teaches you the science behind it — how to use few-shot, zero-shot, and chain-of-thought prompting effectively.

This is literally the only book you need to master prompt engineering for LLMs

Perfect for: Developers working with OpenAI, Claude, or Gemini APIs.

Get the book →

10. Become an LLM Engineer (educative.io)

This is a great skill path to learn all the skills you need to become an AI And LLM engineer in 2025.

It starts with the basics of generative AI and prompt engineering and moves all the way to building intelligent workflows with LangChain, RAG systems, fine-tuning models using LoRA/QLoRA, and developing AI agents with CrewAI.

Key Highlights:

  • Prompt engineering & OpenAI API usage
  • Vector databases for RAG workflows
  • Fine-tuning techniques with LoRA & QLoRA
  • AI Agent creation using CrewAI

Perfect for: Engineers who want to go beyond prompts and start building production-grade GenAI applications.

Here is the link to join this course — Become an LLM Engineer

Conclusion

If you’re serious about becoming an AI engineer or building real GenAI products and AI Agents in 2025, this is your launchpad.

These 10 books and courses will help you master:

  • LLM architecture and deployment
  • AI agents and multi-modal systems
  • RAG and vector databases
  • Prompt engineering and tooling

Start with one, but aim to explore all. As more companies embed AI into their core workflows, developers who can build and ship intelligent systems will lead the future.

By the way, if you want to join multiple course on Udemy, its may be worth getting a Udemy Personal Plan, which will give instant access of more than 11,000 top quality Udemy courses for just $30 a month.

If you got a lot of time and want to save money, Udemy Personal Plan will be perfect for you.

Let’s build the future, one AI agent at a time.

Other AI and Cloud Computing Resources you may like

Thanks for reading this article so far. If you find these Udemy Courses for learning Spring AI from scratch, including tools and libraries then please share with your friends and colleagues. If you have any questions or feedback, then please drop a note.

P. S. — If you want to start from books the start with AI Engineering by Chip Huyen and The LLM Engineering Handbook by Paul Iusztin and Maxime Labonne, both of them are great books and my personal favorites. They are also highly recommend on Redditt and HN.

AI Engineering: Building Applications with Foundation Models

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