Is discrete math interesting?

Discrete math is fun. Many students, especially bright and motivated students, find algebra, geometry, and even calculus dull and uninspiring. Rarely is this the case with most discrete math topics.

Is discrete math needed for algorithms?

Discrete mathematics is a vital prerequisite to learning algorithms, as it covers probabilities, trees, graphs, logic, mathematical thinking, and much more. It simply explains them, so once you get those basic topics, it is easier to dig into algorithms.

Is discrete math easy?

Overall, most students find discrete math to be a hard class when compared to math classes at a similar level such as calculus or linear algebra. This is because discrete math tends to be the first exposure most students have to proofs.

What is the point of discrete math?

Discrete Mathematics provides an essential foundation for virtually every area of computer science, and its applications are correspondingly vast. At the most fundamental level, all of a computer’s data is represented as bits (zeros and ones).

What is taught in discrete math?

Discrete Mathematics. Discrete mathematics is the branch of mathematics dealing with objects that can assume only distinct, separated values. Logic. Logic is the formal mathematical study of the methods, structure, and validity of mathematical deduction and proof.

How important is discrete math for CS?

Discrete Mathematics is the backbone of Computer Science Concepts and notations from discrete mathematics are useful in studying and describing objects and problems in all branches of computer science, such as computer algorithms, programming languages, cryptography, automated theorem proving, and software development.

Should I take discrete math before data structures?

Go ahead and read the data structures book, you’ll be fine. Some topics usually found in introductory discrete math books that come in handy in an algorithms/data structure course are: Some basic probability/statistics: Useful in understanding hashing and randomized algorithms.

Is discrete math used in statistics?

Although discrete statistics are based off of discrete events and probability distributions, these same concepts can be extended to continuous events and probability distributions using concepts from calculus.