Welcome to CMSC 27100! Basic course information can be found on the home page of the course website.
This course is discrete mathematics, to be contrasted with continuous mathematics. Continuous mathematics is the kind of math that people like Euclid (Geometry) and Newton (Calculus) studied, requiring them to come up with notions like irrational numbers. By contrast, we will only be concerned with things like integers and rational numbers, which are conveniently the numbers that we use to count and to program computers.
It is also fundamentally about proof. Proof forms the foundation of mathematics, which in turn formed the foundation of computer science: Turing, von Neumann, Hopper and the other founders of CS were all mathematicians. As a result, every theoretical computer science course you take will have proof at its foundations (and more courses involve deep theory than you may realize).
I don't remember what the world looked like before I studied logic and probability theory, but I imagine it was fuzzy.
There are two good reasons to take this course:
This course will enable you to become a computer scientist. It will give you the foundations to analyze the running time of algorithm (Algorithms), to classify problems according to their difficulty (Complexity Theory) and solvability (Computability Theory). It will allow you to reason about deductive systems (Type Theory), number theory (Cryptography) and stochastic processes (Machine Learning). Ultimately, it will allow you to do computer science.
The other core math course for doing any advanced computer science is Linear Algebra, which forms the basis for key areas of computer science from Machine Learning to Quantum Computing. Unfortunately, we will not have time to cover Linear Algebra in this course, but we highly recommend you take a linear algebra course in the course of your studies.
This course will help you in life. Two of the subjects covered in this course, logic and probability theory, are core to making good decisions in almost every endeavor. While "logic" in our context is not precisely the logic of Mr. Spock from Star Trek (fortunately) or "logic" in its colloquial sense, it is broadly useful. At their core, the arguments you encounter in everyday life approximate the kind of formal logic we will study in this class. Translating these arguments into formal logic will allow you to see holes where they exist and identify fallacies. Probability theory proves even more central to life, from allowing you to win games to helping you assess risk in investing. Probability is essential to a wide variety of endeavors, from allowing you to model elections to balancing risk against rewards in a (hypothetical) pandemic.
This course covers a number of fun areas of (discrete) mathematics.
Keep in mind that while this is an explicit list of content that we expect to cover, there is a lot more that we'll be covering implicitly, in the course of studying these topics. As already mentioned, a big part of this course is to develop your skills in mathematical proof.
I hope you enjoy it!