Artificial Intelligence Engineering roadmap

Machine learning, deep learning, generative AI and MLOps.

Start with AI Foundations & Maths, follow the steps in order, then build a project, prepare for interviews and earn your certificate.

Foundations

1. AI Foundations & Maths — The language of machine learning. What AI engineering is, plus the linear algebra, calculus, probability, statistics and optimisation every model relies on.

Core skills

1. Machine Learning — Models that learn from data. Linear and logistic regression with gradient descent, trees, ensembles, clustering, and rigorous model evaluation.

Advanced

1. Deep Learning — Neural networks that see and hear. Neurons, backpropagation, CNNs, RNNs, optimisers, learning-rate schedules and transfer learning.
2. Transformers & Generative AI — LLMs, RAG and agents. Attention and transformers, large language models, prompting, retrieval-augmented generation, tools and agents.
3. MLOps & Responsible AI — Reliable, fair AI in production. Deployment, monitoring, drift, retraining, fairness, privacy and governance — plus healthcare AI as a case study.

All roadmaps