Resources
If you find yourself asking, "What book should I get to learn $X$?", then you have come to the right place! This is a question I personally get asked a lot, and one that seems to be posted almost daily on several online Math communities, so I put together this list to point out some resources I’ve personally used and found helpful for courses and various other topics.
Disclaimer: in the textbook section, a number of the outgoing Amazon links are affiliate links! These are meant to help cover the hosting cost of this site, but you should also be aware that many of these books are often available at university libraries, at cheaper resalers, or often even as PDFs floating around online.
 Advice

Math Course Resources
 General Notes on Resources
 Single Variable Calculus
 Multiviarable / Vector Calculus
 Linear Algebra
 Ordinary Differential Equations
 Discrete Mathematics
 Number Theory
 Abstract Algebra
 Real Analysis
 Complex Analysis
 Partial Differential Equations
 Numerical Analysis
 Combinatorics
 Probability
 PointSet Topology
 Graduate Real Analysis
 Algebra
 Functional Analysis
 Category Theory
 Algebraic Topology
 Algebraic Geometry
 Differential Geometry / Manifolds
 General Resources
 Fun Stuff
Advice
For Incoming Math Majors

Start thinking about whether or not grad school as an option. You don’t have to decide within your first year, but you’ll want to pick courses accordingly.

Get an idea of what Math is all about  there are great things beyond Calculus!
 To get an idea of what you’re in for as a Math major, take a look at the GRE Mathematics Subject Exam. It covers a broad array of pretty standardized topics.
 Also take a look Garrity’s book (linked in the resources section) for a short, condensed survey of some of the major topics and theorems you’ll encounter.
 One thing that was helpful to me was to make graphs and diagrams of different areas of Math I encountered. Take a look, knowing the landscape you’re traversing is valuable.

Learn Latex and Mathjax early, and then make efforts regularly typeset your written notes.

It may be intimidating, but try to find ways to talk to your professors outside of class! Don’t hesitate to ask for advice on just about anything related to Math or your academic career, in my experience they are always happy to help.

For those aiming for grad school, particularly in pure Math: here are what I would consider some of the most essential, core classes to take:
 Calculus (of course)
 Linear Algebra
 Ordinary Differential Equations
 Abstract Algebra
 Real Analysis
 PointSet Topology
Here are some “nicetohaves” – still important, still beautiful, and great electives, but missing out on them in undergrad isn’t the end of the world:
 Probability
 Combinatorics
 Complex Analysis
 Number Theory
 Discrete Math (e.g. Graph Theory)
 More Linear Algebra (e.g. Numerical Analysis)
Of course, I recommend taking as many Math courses as possible – explore the subject and discover what you like! But the ideas and concepts from these particular courses are relevant to just about any area you might go into, so having some exposure to them makes life much easier (regardless of what you pursue).
On Learning and Being a Student
 Start everything early: Starting early gives you time to mull over questions and potentially visit professors/TAs for help.

Use a wide variety of resources: Books, lectures, notes, PDFs – use them all! The search modifiers
inurl:edu filetype:pdf
on Google are incredibly useful.  Extensively use good resources: There is also some value in working a single, particularly wellregarded book, front to back.
 Spaced repetition: read up on it, and work it into your study habits. Cramming has diminishing returns in proofbased classes, you are much better served by visiting and revisiting material often enough to be familiar with it.
 Sleep like it is your hobby. Two hours of extra sleep is almost always a more efficient use of your time than two hours of tired studying.
On Learning Mathematics Specifically
 Vocabulary: for any new topic, it can be helpful to make a list of definitions and simply memorize them. Math is (at least partially) a language, so it is worth (partially) learning it like one!
 Use multiple books: For most undergraduate topics, there are many “standard” references. Use them all! Crossreference liberally as well.
 Get the definitions down cold: Record every single definition you come across and just do whatever you have to do to memorize them! Some people like flash cards, I personally make a “dictionary” document for each subject. Meaning and understanding is often a gradual process, but knowing the full statement of a definition should just be automatic. I like to think of definitions as the analog “multiplication tables” within higher Mathematics – is it essential to memorize? Well no, but you also wouldn’t want to waste time stopping to multiply out $12^2$ when you’re trying to solve an integral.
 Synthesize often: This includes things like revising class notes, making your own “cheat sheets”, writing up explanations of particular theorems or motivations for certain concepts, etc. Even better, find ways to give talks or teach other people! Present things as if you were trying to teach yourself the topic 612 months in the past.

Google for PDF notes: For just about any topic at any level of specificty, someone has probably written up notes or expository explanations and shared them online. So it can be extremely beneficial to look through the first page or two of Google results using
filetype:pdf
for any concept or proof you happen to be studying and see how other mathematicians think about and present them. 
Work a lot of problems/proofs: Do more than you are assigned, but be judicious with your time! If you stare at a problem for more than an hour or two without making progress, pivot. Sometimes the best way to make progress on a problem is to take a break, work on something different, or sleep on it. A relevant quote from Alexander Grothendieck:
I can illustrate the approach with the image of a nut to be opened. The first analogy that came to my mind is of immersing the nut in some softening liquid, and why not simply water? From time to time you rub so the liquid penetrates better, and otherwise you let time pass. The shell becomes more flexible through weeks and months — when the time is ripe, hand pressure is enough, the shell opens like a perfectly ripened avocado!
 Work the exams, and if possible, do them in a timed setting.
Math Course Resources
General Notes on Resources
Anything lowerdivision: Khan Academy.

On Youtube videos: more and more lectures and talks are being posted online. These vary in quality, but this if offset by the fact that you can watch them at 2x speed.

On video lectures in general: they are a crutch! Use them to supplement and enrich your understanding, but they do not work well as primary resources. The best resources are always materials from your own instructors and courses. Passively watching videos is also not very helpful  take notes, write down timestamps and video titles for important topics, and don’t hesitate to rewatch several times.

MIT OCW: when video lectures are available, generally high quality. Covers a good number of areas, and a good source of practice problems and exams.

Look for book recommendations for your topic/class in places like Math StackExchange (MSE) or MathOverflow (MO), and don’t be afraid to consult multiple books on the same topic. I’ve had very good luck following the referencerequest tags on these sites.

If you find an author/lecturer/general source that you particularly like, look up other things from that source! If they cover other topics, be open to learning those – Math is quite interrelated, and later topics will be easier to learn when you have a collection of concepts you can “hang your hat on”.

For lower division or introductory courses, try to obtain a textbook paired with a solutions manual. This is a great way to drill problems, check your answers, and identify your weaknesses. Beware typos!

Don’t bother with sites like Chegg.

For computational courses: Schaum’s Outlines can be useful, but the quality is very subjectdependent.

Learn how to use a Computer Algebra System (CAS). Don’t use it as a crutch  just learn enough syntax so that you can quickly run “sanity checks” on your computations. Wolfram Alpha is a good for quick things.
 If you have the time, learn something like SageMath, which can do symbolic computations and can even be used for things like group theory and algebra.
Below are resources for specific courses/subjects; I’ve tried to roughly organize these by increasing complexity with respect to a typical undergraduate Math degree.
Legend
 – Textbooks
 – Videos or online lectures
 – Websites or other online collections of resources
 – Particularly excellent resources that I highly recommend
 Details – Expand these sections for notes on the mathematical content or subjectspecific advice.
Single Variable Calculus

Stewart, Calculus: Early Transcendentals
 What can I say? It’s a Calculus book, and it covers the standard curriculum. This one’s a good choice because there are a few solution manuals floating around for older editions.

Spivak, Calculus
 Exposition is a little more advanced, and closer to introductory real analysis. Good for an honorslevel course, or if you want to see a more “rigorous” exposition of the topics from Stewart.

Apostol, Calculus, Vol. 1: OneVariable Calculus, with an Introduction to Linear Algebra
 A good alternative to Spivak.

 Videos of how to solve many specific calculus and engineering problems

 Follows the standard curriculum very closely, with many examples and indepth explanations.
Content
 Todo Notes
 Todo
Multiviarable / Vector Calculus

Schey, Div, Grad, Curl, and All That: An Informal Text on Vector Calculus
 Most textbooks introduce these operators in a very formal way; this text expands and motivates these definitions greatly.

 A very geometric approach, with lots of great imagery!

 More fantastic notes from Paul!
Content
 Todo
Notes
 Many Calculus books cover both single and multivariable, so most of the resources from the single variable section will be applicable here as well. However, the resources in this section focus almost entirely on multivariable cases.
Linear Algebra

Axler, Linear Algebra Done Right
 This subject is usually taught as a bag of computational tricks and algorithms, which obscures the absolute beauty of the subject – this text motivates the theory nicely and shows how powerful it can be.

Goode and Annin, Differential Equations and Linear Algebra
 Good balance of rigor vs. brevity and computation vs. theory. Very concise, gives you what you need to start calculating, but also takes time to list vector space axioms, mentions fields, a nice way of viewing the determinant formula, and (best of all) lists of many conditions that are equivalent to a matrix being singular or nonsingular.

Anton, Elementary Linear Algebra
 Has an entire chapter on many cool applications of Linear Algebra – things like graph theory, computer graphics, and Google’s Pagerank algorithm. Also has a lot of “historical note” blurbs that are pretty interesting.

Strang, Introduction to Linear Algebra
 Strang is a giant in the world of linear algebra, so it’s worth seeing how he approaches the subject.

MIT OCW: Linear Algebra with Gilbert Strang
 Again, it’s Strang, so worth checking out!
Content
 Todo Notes
 Todo
Ordinary Differential Equations

Goode and Annin, Differential Equations and Linear Algebra
 Good precisely because it sets up the language of linear algebra first, making many concepts in ODEs much easier to explain and understand (e.g. solutions as eigenfunctions of derivative operators).

MIT OCW: Differential Equations
 Very Physicsmotivated approach, for better or worse.
Content
 Todo Notes
 Todo
Discrete Mathematics

Rosen, Discrete Mathematics and Its Applications
 Huge variety of topics, good prep for many Mathrelated computer science courses, also just a good survey of many topics at an introductory level.

Grimaldi, Discrete and Combinatorial Mathematics: An Applied Introduction
 Absolutely excellent presentation of recurrence relations, mirroring how solutions of differential equations are found. Also has a good presentation of how to commute quantifiers.

Eccles, An Introduction to Mathematical Reasoning: Numbers, Sets and Functions
 Good for a solid introduction to proofs.

 A wonderful lowerdivision course for which excellent notes have been posted for a number of years.
Content
 Basic logic (truth tables, quantifiers, implications, contrapositive and converse, induction)
 Basic set theory (setbuilder notation, venn diagrams, cartesian products)
 Functions (injectivity/surjectivity, inverse images)
 Relations (partial orders, equivalence relations)
 Basic combinatorics (permutations and combinations, inclusion/exclusion, pigeonhole principle)
 Recurrence relations
 Graphs (Konigsberg problem, Hamiltonian/Eulerian cycles)
 Number theory (divisibility, modular arithmetic, the Euclidean algorithm)
 Generating functions
 Probability (odds for dice rolls and cards, distributions, Stirling’s approximation)
Notes
 Highlight equation aspect of proofs, ties between recurrence relations and ODEs TODO
Number Theory

LeVeque, Fundamentals of Number Theory
 Short but good!
Content
 The prime counting function
 Modular arithmetic, solving equations in rings, multiplicative functions (like the totient)
 The Chinese remainder theorem, Euler’s theorem, Fermat’s Little Theorem
 Quadratic reciprocity, the Legendre and Jacobi symbol
Notes
 This is a subject that pairs very well with introductory abstract algebra (groups and rings).
Abstract Algebra

Dummit and Foote, Abstract Algebra
 Essentially the defacto standard, plus it also serves as an encylopedaic reference.

Beachy and Blair, Abstract Algebra
 A good undergraduatelevel reference.

Matthew Salomone Abstract Algebra Series
 Fantastically wellmotivated series, covers the equivalent of an entire year of material that naturally leads into Galois theory.

Benedict Gross, Lectures at Harvard
 Very clear with lots of examples.

Math Dr. Bob, Abstract Algebra
 I didn’t find these particularly useful, but I know people that have.
Content
 Covers groups, rings, fields, and Galois theory.
Notes
 Todo
Galois Theory

Matthew Salomone, Algebra Lectures
 A portion of his Algebra series, the exposition is fantastic because the series follows a cohesive narrative that introduces some of the major results and benefits of Galois theory early on. Highly recommended.
Content
 Todo
Notes
 Todo
Real Analysis

Rudin, Principles of Mathematical Analysis
 Essentially a standard in undergraduate real analysis, written in a very terse style but covers a great deal of material. Often referred to as “Baby Rudin”.

Francis Su, Lectures from Harvey Mudd College
 Recorded lectures, extremely clear and wellmotivated!

Math Dr. Bob, Real Analysis
 I didn’t find these helpful, but perhaps others will.
Content
 The reals as an ordered field, construction
 Metric spaces, basic topology
 The RiemannStieltjes Integral
 Sequences and series, Cauchy sequences and completeness
 Limits and continuity, pointwise and uniform convergence
 The Mean Value Theorem
 Measure theory and the Lebesgue integral
Notes
 Todo
Complex Analysis

Brown and Churchill, Complex Variables and Applications
 Good overview of computational techniques at an undergrad level.

Needham, Visual Complex Analysis
 Absolutely phenomenal book! The exposition and imagery is truly excellent, although this is perhaps not the best book for learning computations.

Ahlfors, Complex Analysis
 A standard gradlevel reference.
Content
 The complex integral
 Residue theorems
 Analytic vs. Holomorphic vs. Complex Differentiable functions
Notes
 Todo
Partial Differential Equations

Evans, Partial Differential Equations
 A graduatelevel approach.
Content
 Heat/wave/Laplace equations. Notes
 Todo
Numerical Analysis
 Burden, Numerical Analysis
Content
 Fixed points and rootfinding, Newton’s method, least squares.
Notes
 Todo
Combinatorics

Wilf, Generatingfunctionology
 Freely provided by Wilf on his site, exposition is excellent and it provides a comprehensive overview of how to work with generating functions.

Bona, A Walk Through Combinatorics
Content Notes
Probability
 Ross, A First Course in Probability
Content
 Todo
Notes
 It is useful to take (either beforehand or concurrently) introductory classes in both statistics and combinatorics.
PointSet Topology

Munkres, Topology
 A standard  the good stuff starts about 10 chapters in, everything before that is aimed at providing a solid grounding in set theory and proofs.

Lee, Introduction to Smooth Manifolds
 The appendix has a great ubercompressed review of pointset.
Content Notes
 Todo: Specify which chapters are useful. TODO
 Common question: where is Topology useful?
 See Brouwer fixed point theorem, Lie groups in physics, links to functional analysis.
Graduate Real Analysis

Rudin, Principles of Mathematical Analysis
 A contentious standard for real analysis. Chapter 11 has a light overview of measure theory, and the Lebesgue integral.

Rudin, Real and Complex Analysis
 Also referred to as “Papa Rudin”.

Schilling, Measures, Integrals, and Martingales
 This book is not as detailed, as it is geared towards rigorous probability theory, but covers material faster and provides a bit more intuition than Rudin. The first few chapters are a good supplement to a full course.

Folland, Real Analysis: Modern Techniques and Their Applications
 Particularly good for measure theory.

Royden, Real Analysis
 Also good for measure theory.
Content
 Measure theory, sigma algebras
 Monotone and dominated convergence theorems
 $L^p$ spaces, Holder’s inequality
Notes
 Todo
Algebra

Dummit and Foote, Abstract Algebra
 Pretty much the allaround standard, this thing is absolutely encylopedaic!

Atiyah and MacDonald, Introduction to Commutative Algebra

Weibel, An Introduction to Homological Algebra
Functional Analysis

Conway, A Course in Functional Analysis
 Assumes a background around the level of Papa Rudin.
Content
 Measure theory, sigma algebra
 Montone and dominated convergence theorems
 $L^p$ spaces, Holder’s inequality
Notes
 Todo!
Category Theory

Aluffi Algebra Chapter Zero
 Covers Algebra in a more categorical manner, so this book works best as a second pass of Algebra.

Mac Lane Categories for the Working Mathematician
 Seems to be a pretty standard reference; Mac Lane is regarded as one of the founders of the subject.
Content
 Todo!
Notes Expected in some classes, but often assumed. Used in Algebraic Topology and Algebraic Geometry heavily. You can also find many full lectures online by people like Steve Awodey, Bartosz Milewski, and Eugenia Cheng.
Algebraic Topology

Munkres, Topology
 Mostly pointset, but introduces things like the fundamental group in the later chapters.

Hatcher, Algebraic Topology
 Love it or hate it, this seems to be the standard reference!

Bott and Tu, Differential Forms in Algebraic Topology
 A beautiful, wonderful book! Tons of geometric intuition, and has a very deep selection of topics.

Griffiths and Morgan, Rational Homotopy Theory and Differential Forms
 Mostly homotopy theory.

NJ Wildberger, Introduction to Algebraic Topology
 A good undergraduatelevel series, just be aware that he expresses some extremely nonmainstream views in his other videos!
Content
 Todo! Notes
 Todo!
Algebraic Geometry

Reid, Undergraduate Algebraic Geometry
 Great introduction to the field, weaves in a lot of history and classical results.

Hartshone, Algebraic Geometry
 Seems to be regarded as a pretty standard reference.
Content
Notes
Differential Geometry / Manifolds

Spivak, Calculus on Manifolds
 A good followup to Spivak’s Calculus book, the exposition is at an undergraduate level. Worth checking out if you like his style.

Lee, Introduction to Smooth Manifolds
 The gold standard.

Frederic Schuller, International Winter School on Gravity and Light 2015
 This guy is just phenomenal!

Manfredo do Carmo, Riemannian Geometry
Content
 Todo
Notes
 Todo
I’m continually expanding this list – if you have any recommendations, please feel free to let me know in the comments so I can add them!
General Resources
Extracurricular Math

Garrity, All the Mathematics You Missed: But Need to Know for Graduate School
 If you’re thinking about grad school at all, read this! Even if you’re not, it’s a pretty good collection of mathematics that it’s good to at least be familiar with. You can also use this to get an idea of some of the major theorems and results in a variety of subfields.

Introduction to Higher Mathematics
 A great survey that highlights many different areas of advanced mathematics.

Abbott, Flatland
 As the professor who recommended this to me said, reading this book is an absolutely essential step in the professional development of every mathematician. It’s a short fiction that explores a world of 1dimensional beings that live in a 2dimensional universe, which provides a powerful analogy for thinking about higher dimensional objects.
Computer Science

CLRS, Introduction to Algorithms
 MIT OCW: Introduction to Algorithms is a good supplement.

McDowell, Cracking the Coding Interview
 Covers a number of quintessential CS interview questions, worth reading if you are preparing for internships.

Sipser, Introduction to the Theory of Computation
 The standard resource for an introduction to theoretical computer science. Covers things like computability, automata, and Turing machines.

Graham and Knuth, Concrete Mathematics
 An encylopedaic reference for a huge swath of discrete Mathematics.
The Math Subject GRE
If you are thinking about applying to graduate school in Mathematics (pure or applied), I would recommend that you start looking at the material for this exam within your first few years, and take it as soon as your Junior year.
Note that the Math Subject GRE is vastly different than the Math portion of the General GRE. The latter covers primarily highschool level mathematics and requires no courses beyond Calculus (although the questions can still be tricky). The former is over 50% Calculus, and often includes a wide variety of upperdivision topics as well. Many sources confuse these two exams!
Topics
 Single Variable Calculus
 Multivariable Calculus
 Ordinary Differential Equations
 Linear Algebra
 Complex Analysis
 Abstract Algebra
 Primarily groups and rings, virtually no module or Galois theory.
 Probability/Statistics
 Real Analysis
 Convergence of sums/sequences, topological properties of $\RR$.
 Combinatorics
 Graph theory, counting problems
 PointSet Topology
 Numerical Analysis
 Set Theory and Logic
Resources
 You can find five sample exams here.
 Princeton Review, Cracking the Math Subject GRE
Advice
 Most problems don’t require extensive computations; there is usually a trick that solves it very quickly.
 Time is the most difficult factor, be sure to take timed practice tests. You have right around two minutes per problem.
 Sign up early, as these exams are often only held a few times per year.
Fun Stuff

 A cool little dungeon crawler in which the ingame world is a hpyerbolic space.

Eversion of Spheres: Part 1 and Part 2
 A great way to get some visual intuition for what homeomorphisms and/or homotopy equivalences might look like

Funny papers, notes, or expository writing

Some interesting Mathrelated movies:
 Proof
 Good Will Hunting
 A Beautiful Mind (John Nash)
 The Imitation Game (Alan Turing)
 The Theory of Everything (Stephen Hawking)
 The Man Who Knew Infinity (Srinivasa Ramanujan)
 Proof
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