5 Free Courses to Learn AI Engineering

AI engineering sits somewhere between software engineering, machine learning, and generative AI.

As an AI engineer, you are not usually training a foundation model from scratch. Most of the time, you are taking existing models and figuring out how to turn them into useful applications and automated systems.

That can mean working with model APIs, embeddings, vector databases, retrieval-augmented generation (RAG), AI agents, multi-agent workflows, evaluation systems, model serving, monitoring, and deployment. You might build agents that use tools, coordinate with other agents, automate internal workflows, or handle parts of a larger business process.

The good thing is that you do not need an expensive bootcamp to learn all of this. Some of the best AI engineering courses are completely free and open-source, with lectures, notebooks, exercises, and projects available online.

I have ordered the following five courses from easiest to most difficult, so you can also follow them as a learning path and gradually build your skills.

1. Hugging Face Large Language Model Course

If you are relatively new to large language models (LLMs), I would start with the Hugging Face LLM Course.

The course starts with Transformer fundamentals and gradually moves into the Hugging Face ecosystem, including Transformers, Datasets, Tokenizers, Accelerate, and the Hugging Face Hub. You also learn how to fine-tune models, build demos, curate datasets, and work with reasoning models.

The curriculum includes:

• Transformer models
• Using Hugging Face Transformers
• Fine-tuning pretrained models
• Datasets and Tokenizers
• Classical natural language processing (NLP) tasks
• Building and sharing demos
• Dataset curation
• LLM fine-tuning
• Reasoning models

The course is completely free and requires good Python knowledge. Prior PyTorch or TensorFlow experience is helpful but not required.

What makes it a good starting point is that you learn how LLMs actually work before moving into higher-level areas such as RAG and AI agents.