1. The basics of economics - An introductory course covering topics like complements and substitutes is vital for working in the greater economy, or just simply understanding it. While the concept of a Giffen Good won’t necessarily help you, knowing about externalities will. It might also help you appreciate that more situations are win-win than you might have realized.
2. How to write a proof - All computer science majors should know how to write a proof. And discrete math, while a part of a well balanced breakfast, doesn’t count. [Induction is just one proof technique, and you can get by without actually knowing much about proofs.] A course in algebra or real analysis is necessary to really write proofs. And by algebra I mean group theory or abstract algebra, not the course you took in high school. For the full benefit, take algebra and real analysis in the same term.
Why is proof writing essential? Because it’s programming! Think about when you first learned how to program: if a task required an “if” and a loop, you might not have had any intuition on where to put them in relation to each other. But now the same task would feel completely natural. Writing a proof is very similar. There is a set of tricks that you learn, and once you learn them things look quite different.
3. How to write - Written communication skills are essential, whether you’ll work in the industry or academia. It’s best if you can find a mechanics course, and not a writing course that is effectively about a different topic. That is, many schools will try to make the writing courses more relevant or interesting by making it be about a special topic. Try to go for the “boring” version of the course.
4. Probability and statistics - There are some things that you’ll only pick up properly by taking a course. Together with the CS major requirements (which should give you discrete math, single variable and multiple variable calculus, and linear algebra) and algebra and/or real analysis, picking up statistics will probably give you a minor in math. Learning statistics can help you work with other scientists on their projects.
5. The current hot topic - In previous decades, it might have been databases, or object-oriented programming. Today it might be web programming or service-oriented architecture. Whatever the current fad is, be sure to take a course in it. If only to see what the fad is about.
6. The halting problem - Most problems cannot be solved by machines. This is a fairly deep idea that our culture has absorbed so well that it no longer sounds shocking. The same goes with radio, Goedel, and the atomic bomb; it wasn’t until postmodern art and the cold war that we could once again cope with these concepts. However, taking a course in computability theory can re-sensitize you to this pretty amazing proof.
7. Pure functional programming - You most likely won’t go into pure functional programming, unless you do research in it or work for a select few companies, but knowing it will help you be a better programmer. The reason is that you will learn many new forms of abstraction, and concepts like Church numbers and continuations and monads and, yes, recursion, and these tools can be applied to your next Java program too.
8. P and NP - OK, this one is already on your critical path, but pay attention anyway. You want to be sure you can correct someone when they incorrectly call NP “non-polynomial.” As if!
9. The topics from the course you’re sure to hate - This could be a CS course you find too-low-level, too-theoretical, or a non-CS course you find too-objectionable, too-hard, or too-boring. If a course like this seems to be an issue for you, and you find yourself explaining to others why you’re so glad you don’t have to take so-and-so, it should tell you that you’ll learn a lot by taking the course! Perhaps you won’t learn the materials of the course, but you’ll learn about your own limits and perhaps more about the justifications you make to yourself. [Hint: They are usually weak.]
10. The non-CS course you’re sure to love - In the end, you should have some fun. This is the course you’ll probably get the least out of, but take it anyway. Do it once. If you happen to love many courses, then good for you, but be sure it doesn’t get in the way of covering the rest of the courses on this list.
My approach here has been practical, based on courses you can actually take. I’ll save a rant on what courses should be available for a different day. I omitted some obvious choices, like a course on logic, even though logic is essential for a computer scientist. Why not recommend it, then? Because taking a course in logic won’t make you more logical! We can’t conflate the two concepts. And I believe this conflation is the reason why many lists about “what colleges should be teaching” are so often off the mark. Instead, I’ve focused on learning objectives that are likely to be learned.