Become an AI Engineer — Free
AI Engineering is the fastest-growing role in tech right now. Unlike ML researchers who train models from scratch, AI Engineers build products using existing models — the OpenAI API, open-source models on Hugging Face, LangChain agents, and RAG pipelines. The tools are accessible, the demand is enormous, and the best learning resources are entirely free.
Your Step-by-Step Path
Step 1: Python Foundations
Python is the language of AI engineering. You need a solid foundation before working with AI APIs and libraries.
CS50's Introduction to Programming with Python
36h · Free
Step 2: How LLMs & AI Actually Work
Understand what large language models are, how they generate text, and why prompting matters before you start building.
Introduction to Generative AI
1h · Free
Step 3: Prompt Engineering
Learn to communicate effectively with AI models. Prompt engineering is the core skill every AI engineer needs.
ChatGPT Prompt Engineering for Developers
1h · Free
Step 4: Build AI Apps with LangChain
LangChain is the leading framework for building LLM-powered applications. Learn chains, agents, memory, and tools.
LangChain for LLM Application Development
3h · Free
Step 5: RAG — Retrieval-Augmented Generation
Make AI answers accurate and grounded by connecting models to your own data with vector search and retrieval.
Building and Evaluating Advanced RAG Applications
2h · Free
Step 6: Open Source AI with Hugging Face
Go beyond the OpenAI API — use and fine-tune open-source models from the world's largest AI model hub.
Hugging Face NLP Course
30h · Free
More Courses to Explore
Google's beginner-friendly introduction to generative AI. Learn what generative AI is, how it differs from traditional machine learning, and how to create your own AI applications with Google tools.
Google's overview of large language models (LLMs). Covers what LLMs are, their use cases, prompting techniques, and how to tune LLMs for specific tasks using Google tools.
freeCodeCamp's comprehensive introduction to generative AI covering the OpenAI API, Gemini Pro, LangChain, RAG basics, and building real AI-powered apps. Completely free on YouTube.
A hands-on short course from DeepLearning.AI and OpenAI. Learn to use LLMs to build powerful applications. Covers best prompt engineering practices, summarising, inferring, transforming text, and chatbots. Taught by Andrew Ng. Completely free.
Harvard's introduction to AI with Python. Covers search, knowledge representation, uncertainty, optimisation, machine learning, neural networks, and NLP.
The definitive short course on building with LangChain, taught by its creator Harrison Chase alongside Andrew Ng. Covers document loading, splitting, vector stores, retrieval, and agents. Free.