5 Free Courses to Learn AI Engineering

If you are starting from scratch, I would begin with the Hugging Face LLM Course to understand Transformers, tokenization, inference, and fine-tuning.

From there, move into AI Engineer Notebooks and LLM Zoomcamp to start building real LLM applications. Once you are comfortable with that, take MLOps Zoomcamp to learn deployment, monitoring, pipelines, and production systems. Finally, use Maxime Labonne's LLM Course to go deeper into fine-tuning, quantization, inference optimization, and open-source models.

The important part is to keep building as you learn.

Even in a world where you can ask an AI coding agent to generate an application, fundamentals still matter. You need to understand the code, debug failures, make architecture decisions, deploy systems, monitor them, and know what to do when something breaks.

AI is making it easier to build software, but that does not remove the need for engineering skills. Companies still need strong software engineers, machine learning engineers, MLOps engineers, and infrastructure engineers who can take an idea all the way into production.

Use AI to move faster, but build enough knowledge and hands-on experience that you understand what the AI is building for you. That combination is what will make you a much stronger AI engineer.

Abid Ali Awan (@1abidaliawan) is a certified data scientist professional who loves building machine learning models. Currently, he is focusing on content creation and writing technical blogs on machine learning and data science technologies. Abid holds a Master's degree in technology management and a bachelor's degree in telecommunication engineering. His vision is to build an AI product using a graph neural network for students struggling with mental illness.