A Math + CS DoubleMajor Schedule at Caltech
Like most students at Caltech, I spent most of my waking hours doing problem sets. I was a Math + CS doublemajor, a decision that extended those waking hours. Scroll down to see my course list.
Because I was a "CSmajor first", the math major was a lot more difficult. I didn't have a lot of experience with math contests or problemsolving as an undergraduate, and I also missed several earlymorning lectures. Here are some opinions if you are also a CS major thinking about adding math (note: these are specific to Caltech).
Reasons to add math

Because you want to see "Math and Computer Science" on your diploma. That's a really shallow reason, but if you want it (I did), you should go for it, and don't let anyone tell you otherwise!

Because the math might be relevant later. Because Caltech's math curriculum is covers algebra, analysis, and topology, you get a solid exposure to each one. A lot of this stuff shows up in computer science in unexpected ways. For example, the BrescampLieb Inequality is used to prove lower bounds for the memory movement costs of matrix multiplication.

Because you want to get better at writing proofs. After a ton of problem sets, it becomes second nature. You also get better at collaborating with others and explaining your work. If you choose to LaTeX your sets, you become better at that too.
Reasons not to add math

It consumes nearly all your free course slots. You'll lose a lot of freedom choose courses that are interesting to you, and you'll have to take certain classes at certain times, since they won't be offered otherwise. Being an undergraduate is probably the only time you get to study whatever you want. Do you really want to spend it jumping through hoops?

It eats up professional and personal time. If I hadn't added the math major, I would have spent the extra time preparing for technical interviews, doing computer science research, and spending time with my friends. Instead, I spent that time solving problems in algebra or complex analysis, most of which I have forgotten.

It doesn't help much for graduate school admissions. For computer science at least, I think graduate schools care more about your research and recommendation letters than whether you took the hardest math class out there.
I regret nothing! Here's my undergraduate schedule:
Advanced Placement
Ma1A Calculus of One and Several Variables & Linear Algebra 
Ma1C Calculus of One and Several Variables & Linear Algebra (Multivariable) 
Ph1A Classical Mechanics and Electromagnetism 
Fall 2016
CS1 Intro. to Computer Programming 
CS9 Intro. to Computer Science Research (Pizza Class) 
Ch1A General Chemistry 
En25 The Rhetoric of Superiority 
Ma2 Differential Equations 
Ma6A Intro. to Discrete Mathematics 
Winter 2017
CS2 Intro. to Programming Methods 
CS21 Decidability and Tractability 
Ch1B General Chemistry 
Ph11B Freshman Seminar: Research Tutorial 
Ma1B Calculus of One and Several Variables and Linear Algebra 
Spring 2017
Bi1 Principles of Biology 
CS38 Intro. to Algorithms 
Ge1 Earth and Environment 
H2 Baseball and American Culture, 1840 to the Present 
Ph1C Classical Mechanics & Electromagnetism 
Fall 2017
CS11 Computer Language Lab 
CS121 Relational Databases 
CS177A Discrete Differential Geometry: Theory & Applications 
CS156A Learning Systems 
Ma5A Intro. to Abstract Algebra 
PS12 Intro. to Political Science 
Winter 2018
CS155 Machine Learning / Data Mining 
CS4 Fundamentals of Computer Programming 
Ec11 Intro. to Economics 
Ma5B Intro. to Abstract Algebra 
Ph2B Waves, Quantum Mechanics, and Statistical Physics 
Spring 2018
CS24 Intro. to Computing Systems 
CS153 Current Topics in Theoretical Computer Science (Communication Complexity) 
CS156B Learning Systems 
L103C Intermediate French 
Ma5C Intro. to Abstract Algebra 
Fall 2018
CS11 Computer Language Lab: ACMICPC 
CS80A Undergraduate Thesis 
CS150 Probability & Algorithms 
En102 Origins of Science Fiction 
Ma108A Classical Analysis 
Ma177A Computability Theory 
Winter 2019
ACM216 Markov Chains, Discrete Stochastic Processes and Applications 
CS90 Undergraduate Reading in Computer Science 
Ch3X Experimental Methods in Solar Energy Conversion 
Ec112 Bayesian Statistics 
Ma177B Computability Theory 
PE6 Core Training, Beginning/Intermediate 
Spring 2019
CS90 Undergraduate Reading in Computer Science 
CS115 Functional Programming 
CS151 Complexity Theory 
En89 Writing the News  Journalistic Writing 
Ma108C Classical Analysis 
Fall 2019
APh9A SolidState Electronics for Integrated Circuits 
CS90 Undergraduate Reading in Computer Science 
EE126A Information Theory 
Ec105 Firms, Competition, and Industrial Organization 
Ma10 Oral Presentation 
Ma109A Intro. to Geometry and Topology 
Winter 2020
EE10A Intro. to Digital Logic and Embedded Circuits 
En86 Fiction and Creative Nonfiction Writing 
En117 Picturing the Universe 
Ma109B Intro. to Geometry and Topology 
Ma140 Probability 
PE10 Aerobic Dance 
Spring 2020
H134 Birds, Evolution, Speciation and Society 
Ma109C Intro. to Geometry and Topology 
Ma6C Intro. to Discrete Mathematics 
Ph2C Waves, Quantum Mechanics, and Statistical Physics 
SEC11 Written Academic Communication in Engineering and Applied Science 
VC72 Data, Algorithms, and Society 