Learning paths: Machine Learning worked examples
Choose prerequisites and a sequence of skills with concrete checkpoints.
Learning paths
Choose prerequisites and a sequence of skills with concrete checkpoints.
Where to start with machine learning: a beginner's four-step path
Start machine learning with a four-step learning path: Python, data tools, maths and statistics, then models. Check your progress with practical tasks.
learning path · 8 min readHow to learn AI from scratch: a practical beginner's plan
Learn AI from scratch with a week-by-week plan: Python, data tools, maths, statistics, a first machine learning model and a small generative AI project, with a checkpoint for each stage and free resources.
learning path · 11 min readMachine learning engineer roadmap: seven stages, each with a checkpoint
A machine learning engineer roadmap in seven stages: Python as software, data tools, the maths a model uses, classical ML, production habits, deep learning and a portfolio. Each stage links to free lessons and ends in a checkpoint.
learning path · 11 min readHow to get an AI or machine learning internship: what to learn, build and explain
A student's plan for an AI or machine learning internship: the foundations interviewers test, two projects worth building, the questions your project will raise, and how to apply without overclaiming.
learning path · 7 min readAI engineer vs machine learning engineer: the difference, and what to learn for each
A machine learning engineer trains and deploys models; an AI engineer builds products on existing models. How the work, skills and maths differ, the foundations both share, and a learning order for each.
comparison · 7 min read