MIT OCW 18.06 Linear Algebra

Category

Math / Statistics / Numerical Methods

Provider

MIT OCW

Type

course

Level

foundation

Topic

Math / Statistics / Numerical Methods

Track

Math / Statistics / Numerical Methods

Section

n/a

Format

n/a

Status

publishable

Commercial

unknown

Featured

no

Fast start

no

Sequence

n/a

Priority

n/a

Primary source

learning_paths

Sources

learning_paths, website_existing

ID

3209ed37cc58c6af

MIT 18.06 Linear Algebra

MIT OCW

The canonical linear algebra course for ML, graphics, controls, robotics, and quantum work.

MIT OCW 18.01 Calculus

ocw.mit.edu

MIT OCW 6.006 Introduction to Algorithms

MIT OCW

Data structures and algorithms for high-performance systems.

Stat 110: Introduction to Probability

Harvard

Probability tools needed for ML evaluation, uncertainty, and inference.

MIT 18.05 Probability and Statistics

MIT OCW

Needed for inference, uncertainty, Bayes, RL, decision-making, and experimentation.

MIT OCW 6.003 Signals and Systems

MIT OCW

Fourier/Laplace, sampling, LTI systems, and core signal intuition.

MIT OCW 8.20: Introduction to Special Relativity

MIT OCW

Modern physics foundations: spacetime, relativistic dynamics, and intuition.

MIT OCW 6.451 Principles of Digital Communication II

MIT OCW

Advanced digital communications topics (multiuser, coding, detection).

MIT OCW 6.450 Principles of Digital Communications I

MIT OCW

Information theory + digital comm fundamentals for modern RF/LLM-era signal systems.

MIT OCW 6.02 Digital Communication Systems

MIT OCW

Coding, modulation, synchronization, and end-to-end digital comms.

SciPy Contributing Guide

SciPy

Upstream-quality scientific Python contribution practices.

MIT OCW: Introduction to Neuroscience

MIT

Adds rigorous structure to the fundamentals and links well to quantitative work.