Math for Machine Learning
7 lessons
What you'll learn

Unit 1
Vectors and Dot Products
7 lessons
- Vectors as lists of features
- Dot products measure alignment
- Norms and the length of a vector
- Compute dot products and lengthsChallenge
- Cosine similarity between embeddings
- Rank three embeddings by similarityExercise
- Vectors and dot products reviewUnit review
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Law
Legal literacy — how law actually works. The trunk gives you the operating system: where law comes from, how courts and precedent work, contracts, torts, property, criminal vs civil, and constitutional structure. Clusters dive into reading cases, contract mechanics, IP, your rights with police, and the startup legal toolkit.
Cybersecurity
A working understanding of cybersecurity — how attackers operate, how defenders push back, and the moving parts of every modern security program. The trunk gives you the throughline from threat model to defense to response; clusters dive into cryptography, network defense, web application security, secure coding, penetration testing, incident response, cloud security, and governance.
Economics
A working understanding of how economies actually behave — how scarcity drives choice, how markets allocate resources (and fail to), how money and policy steer the macroeconomy, and how trade, behavior, and institutions shape long-run prosperity. The trunk gives you the throughline a literate citizen needs; clusters dive into elasticity, market failures, consumer/producer theory, monetary and fiscal policy, trade policy, behavioral finance, and economic history.
Programming
A practical track that takes you from zero to shipping working software. The trunk gives you the throughline — how to think in code, write a program, and put it in front of users — and clusters dive deep into thinking tactics, Python craft, engineering for change, real-world shipping, and working alongside AI assistants without letting them put garbage in your codebase.
Natural Science
A working understanding of the natural world — what science is, how matter and energy behave, how life persists and changes, and how Earth and the cosmos fit together. The trunk gives you a single coherent throughline across physics, chemistry, biology, and earth/space science; clusters dive into experimental design, mechanics, thermodynamics, electromagnetism, modern physics, genetics, ecology, and climate.
Finance & Investing
A working understanding of finance and investing — how capital markets price risk, how companies create value, how investors build portfolios, and where the math meets human psychology. The trunk gives you the throughline; clusters dive into financial statements, valuation, corporate finance, bonds, portfolio construction, derivatives, and behavioral finance.
Frequently asked questions
What does the Math for Machine Learning roadmap cover?
1 unit: Vectors and Dot Products.
How do I start the Math for Machine Learning roadmap?
Get the Mochivia app on the App Store and open this roadmap there.