MIT study guides, course by course
MIT's curriculum is built around problem sets — psets — graded on rigor, with required core classes (the GIRs) like 8.01 and 18.01 that every student takes regardless of major. Because MIT publishes full courses on OpenCourseWare, numbers like 18.06 and 6.006 are searched by self-learners worldwide, who face the same study challenges as enrolled students minus the deadlines.
MIT numbers everything: departments are numbers (Course 6 is EECS, 18 is Math, 8 is Physics), and classes are department.number — 6.006, 18.06, 8.01. Credits are "units" (a typical class is 12 units, roughly 12 hours a week). Many of these exact course numbers are world-famous through MIT OpenCourseWare, where the materials are free.
Fennie is independent and not affiliated with MIT.
Use Fennie at MITElectrical Engineering & Computer Science
6.100A — Introduction to Computer Science Programming in Python
6.100A — formerly 6.0001, the number most search results still use — is MIT's half-semester introduction to programming in Python for students with little or no experience. The 6.0001 lectures on OpenCourseWare are among the most popular free programming courses anywhere.
6.006 — Introduction to Algorithms
6.006 is MIT's core algorithms class — sorting, hashing, trees, graph algorithms, shortest paths, and dynamic programming — emphasizing both rigorous analysis and Python implementation. Its OpenCourseWare lectures are a global standard for learning algorithms and prepping technical interviews.
6.046J — Design and Analysis of Algorithms
6.046J — renumbered 6.1220 in MIT's current catalog, but still searched overwhelmingly by its old number — is the advanced algorithms course following 6.006: divide and conquer, randomized algorithms, amortization, network flow, approximation, and complexity. The OCW lectures are a staple for advanced self-study.
6.042J — Mathematics for Computer Science
6.042J — now numbered 6.1200J — is MIT's discrete math course for CS: proofs, induction, number theory, graph theory, counting, and discrete probability. Its OCW versions, with full lecture videos and the famous free textbook, make it one of the most-used discrete math resources in the world.
6.1010 — Fundamentals of Programming
6.1010 — formerly 6.009, the number much of the internet still uses — is MIT's second programming course, where Python fluency from 6.100A gets turned into real software through substantial weekly labs: audio processing, image filters, graph search, interpreters. It's the bridge between knowing Python and engineering with it.
6.1020 — Software Construction
6.1020 — formerly 6.031, whose public course readings are a renowned free resource — teaches writing software that's safe from bugs, easy to understand, and ready for change: specifications, testing, abstract data types, and concurrency. It's MIT's software engineering foundation, taught in recent terms in TypeScript after years in Java.
6.036 — Introduction to Machine Learning
6.036 — renumbered 6.3900 in the current catalog but still searched overwhelmingly by its old number — is MIT's introductory machine learning course: perceptrons, gradient descent, neural networks, and reinforcement learning basics, with the OCW version serving a huge self-study audience.
6.824 — Distributed Systems
6.824 — renumbered 6.5840, but famous worldwide by its old number — is MIT's graduate distributed systems course: fault tolerance, replication, and consistency, taught through research papers and a legendary sequence of Go programming labs including MapReduce and Raft. Its free lectures and lab materials make it the standard self-study path into distributed systems.
6.0002 — Introduction to Computational Thinking and Data Science
6.0002 is the half-semester sequel to 6.0001 — optimization, simulation, Monte Carlo methods, and a first taste of machine learning — and through OCW and edX it's one of the most-taken data science introductions in the world. In MIT's current catalog the material lives on as 6.100B.
Mathematics
18.01 — Single Variable Calculus
18.01 is MIT's single-variable calculus GIR — limits, differentiation, integration, and infinite series — required of every MIT student without prior credit. The OCW version, including David Jerison's lectures, has taught calculus to millions of self-learners.
18.02 — Multivariable Calculus
18.02 is MIT's multivariable calculus GIR: vectors, partial derivatives, multiple integrals, and vector calculus through Green's, Stokes', and the divergence theorems. It's required for every MIT student and is among the most-viewed math courses on OpenCourseWare.
18.06 — Linear Algebra
18.06 is MIT's linear algebra course, made world-famous by Gilbert Strang, whose OCW lectures are arguably the most beloved math course recordings ever published. It covers systems of equations, vector spaces, orthogonality, determinants, eigenvalues, and the SVD with Strang's signature intuition-first style.
18.03 — Differential Equations
18.03 is MIT's differential equations course — first and second order ODEs, Laplace transforms, Fourier series, and linear systems — required by most engineering and science majors and among the most-used math courses on OpenCourseWare, where Arthur Mattuck's lectures are a classic.
18.05 — Introduction to Probability and Statistics
18.05 is MIT's introduction to probability and statistics — probability models, random variables, Bayesian and frequentist inference, and regression — taught in a celebrated flipped, problem-centered format whose complete materials on OCW make it one of the most recommended statistics self-study courses anywhere.
18.100A — Real Analysis
18.100A is MIT's introductory real analysis course — the construction of the real numbers, sequences and series, continuity, differentiation, and the Riemann integral, all proved from scratch. It's most students' first fully rigorous math course, and its OCW version with full lecture videos has a devoted self-study following.
18.600 — Probability and Random Variables
18.600 — formerly 18.440 — is MIT's core probability course: combinatorics, random variables, the named distributions, expectation, limit theorems, and martingales, taught with full mathematical depth. It's the standard probability foundation for math majors, quants-in-training, and 18.05 graduates who want the real machinery.
Physics
8.01 — Classical Mechanics
8.01 is MIT's calculus-based classical mechanics GIR — kinematics, Newton's laws, energy, momentum, rotation, and oscillations — required of every first-year student. Its OCW materials make it a benchmark mechanics course for self-learners and ambitious high schoolers worldwide.
8.02 — Electricity and Magnetism
8.02 is MIT's electricity and magnetism GIR, covering electrostatics, circuits, magnetism, induction, and Maxwell's equations using multivariable calculus. It's the second required physics course for all MIT students and a heavily used OCW resource.
8.03 — Vibrations and Waves
8.03 is the third course in MIT's physics sequence — oscillators, coupled systems, waves on strings, sound, and electromagnetic waves through interference and diffraction. Its OCW versions, with full lecture videos and famously demonstration-rich teaching, make it a staple for physics self-learners after 8.01 and 8.02.
8.04 — Quantum Physics I
8.04 is MIT's first quantum mechanics course — wave-particle duality, the Schrödinger equation, one-dimensional potentials, tunneling, and the hydrogen atom. Allan Adams' OCW lectures for 8.04 are among the most-watched physics courses on the internet, drawing self-learners far beyond MIT.
Chemistry
5.111 — Principles of Chemical Science
5.111 is MIT's general chemistry GIR option, covering atomic structure, quantum concepts, bonding, thermodynamics, equilibrium, acid-base chemistry, kinetics, and transition metals — with biological and medical examples woven throughout. Its OCW version is a popular free gen-chem course.
5.12 — Organic Chemistry I
5.12 is MIT's first organic chemistry course — structure and bonding, stereochemistry, and the core reaction mechanisms of organic molecules. It's the gateway to the chemistry and chemical biology majors and a pre-med staple, with OCW versions providing notes and exams for self-learners.
Biology
Economics
14.01 — Principles of Microeconomics
14.01 is MIT's introductory microeconomics course — supply and demand, consumer and producer theory, market structures, and welfare economics, taught with more mathematical directness than most intro courses. Its OCW versions, with full lectures and exams, are among the most-used free economics courses in the world.
14.02 — Principles of Macroeconomics
14.02 is MIT's introductory macroeconomics course — national accounts, the goods and money markets, unemployment, inflation, expectations, and open-economy dynamics — built around working models rather than narratives. Its OCW materials serve a large global audience of students and self-learners.
Materials Science & Engineering
Studying at MIT?
Upload your course materials and Fennie generates Daily Plans paced to your deadlines — plus chat, flashcards, and quizzes built from your own courses.
Get started free