OPEN COURSES · SUBJECT GUIDES · INDEPENDENT STUDY
Open Curriculum
A DIRECTORY FOR LEARNING
UNIVERSITY COURSES. CONNECTED LEARNING.

University courses.
Ideas that connect.

Discover courses by subject, meet their instructors and understand the prerequisites. Follow a considered route from first principles to deeper understanding.

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22Selected courses
6Subject areas
4Source institutions
OPEN COURSE COLLECTION
OPEN CURRICULUM / ACADEMIC COLLECTION

Public course materials from

StanfordUniversityMITHarvardUniversityYaleUniversity
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SELECTED COURSES

A place to begin

All courses
01 / OCCS229
Stanford · Artificial intelligence

Machine Learning

Andrew Ng

AdvancedExplore course
11 / OC18.06
MIT · Mathematics & statistics

Linear Algebra

Gilbert Strang

IntroductoryExplore course
EXPLORE BY SUBJECT

Explore a field of study

Subject index
01 / OC

Artificial intelligence

6 courses · From machine learning foundations to vision, language and decision systems.
02 / OC

Computer science

4 courses · Build programming fluency and the ability to think in abstractions.
03 / OC

Mathematics & statistics

5 courses · Explore the shared language of vectors, change, probability and optimization.
04 / OC

Humanities & society

3 courses · Examine how people, ideas and economic systems interact.
05 / OC

Design & interaction

2 courses · Turn an understanding of people into useful digital experiences.
06 / OC

Algorithms & systems

2 courses · Understand how programs work and how to solve problems efficiently.
CONNECTED LEARNING

A course is a starting point

Connect courses through their prerequisites and build an adaptable sequence for independent study.

All study paths
FEATURED PATH / MATHEMATICS × COMPUTING

Foundations of machine learning

This route is for learners who want to understand machine learning systematically. Begin with small programming tasks, then develop the matrix and statistical foundations.

Explore the path
01

Introduction to Computer Science and Programming in Python

MIT · 6.0001
02

Linear Algebra

MIT · 18.06
03

Statistics for Applications

MIT · 18.650
04

Machine Learning

Stanford · CS229

A first course of study in computing

Move from first programs to abstractions, algorithms and systems.

4 courses
03 / OC

Understanding people and interaction

Connect perspectives from psychology with design and development.

3 courses
03 / OC
PEOPLE & IDEAS

Meet the people behind the courses

All instructors
AN

Andrew Ng

Stanford · 2 listed courses

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GS

Gilbert Strang

MIT · 1 listed course

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PB

Paul Bloom

Yale · 1 listed course

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DM

David J. Malan

Harvard · 1 listed course

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THE LEARNING JOURNAL

Notes for independent study

More from the journal
01 / OC
Study practice

Read the syllabus before you begin

A syllabus is a map of the course. Establish the goals, prerequisites and organization of materials before playing the first lecture.

5 min read
02 / OC
Course planning

What mathematics comes before machine learning?

Instead of extending preparation indefinitely, build a short mathematics checklist around concrete problems.

6 min read
03 / OC
Learning plans

Make room for a course in your week

A sustainable schedule needs specific tasks and room for adjustment. Start with a weekly plan you can keep.

4 min read

Choose the question. Find the course.

Search by subject, level or instructor to find a useful next step.

Open the course directory