Are Mathematics and Physics THAT Important for Computer Science?

29 Sep 2022

Articles

Computer Science is a large subject that is said to group up a lot of subjects within. It is a large gray area for many who ponder on what computer science actually focuses on. According to the Department of Computer Science, principal areas of study within Computer Science include artificial intelligence, computer systems and networks, security, database systems, human computer interaction, vision and graphics, numerical analysis, programming languages, software engineering, bioinformatics and theory of computing. The problems that many computer scientists face ranges from determining what problems can be solved with computers and the complexity of the algorithms of the solution, to designing applications that perform well on handheld devices that meet certain needs / requirements. Thus, there are many basics that are needed for a certain area of study. In this article, we are going to focus on whether mathematics and physics are THAT important for computer science.

Mathematics deals with the logic of shape, quantity and arrangement. Mathematics is considered to be the basics in everything that we do. Of course not everything within mathematics would be used in computer science, especially for those aspiring and first year professionals. One of the more basic mathematics is Discrete mathematics. It analyzes the relationship between things that are distinct and separate. The concepts of discrete math include: Probability, Logic, Number theory, Graph theory. This field of mathematics is mainly used to test out and learn which algorithm is considered more efficient.

Another field of mathematics is statistics. With the large amount of data that is available, it has become more important to be able to learn from it, especially in machine learning. This increased reliance on data has made statistics an important topic of study for all computer science students. Understanding statistics can make it easier to grasp concepts like: Data mining, Machine learning, Future modeling, Speech recognition, User responsiveness, Computer graphics analysis.

The third main field of mathematics is Algebra. Algebra covers various concepts, including linear equations, operations, factoring, exponents, polynomials, quadratic equations, rational expressions, radicals, ratios, proportions, and rectangular coordinates.Algebra is used in computer science in the development of algorithms and software for working with mathematical objects. It is also used to design formulas that are used in numerical programs and for complete scientific computations.

Calculus is another field in mathematics that is often used. This is often used in computer graphics, scientific computing, and computer security. Linear algebra, number theory, and graph theory are some of the math courses for machine learning to software engineering. These 3 fields are the major field that often comes up when learning computer science. There are more fields, however, they do not play / come out as often as these three.Calculus is another field in mathematics that is often used. This is often used in computer graphics, scientific computing, and computer security. Linear algebra, number theory, and graph theory are some of the math courses for machine learning to software engineering. These 3 fields are the major field that often comes up when learning computer science. There are more fields, however, they do not play / come out as often as these three.

Physics, on the other hand, is more complex and plays a role in more hardware heavy topics within computer science. This is not something that is often classified into computer science as they slowly become more to computer engineering. A basic understanding of physics would be needed especially if you are taking your bachelors in computer science. Physics is taught in computer science, mainly, to give students a better understanding of how the physical world works and how it can be applied to computer science.Physics provides a foundation for understanding more advanced concepts in computer science, such as artificial intelligence and quantum computing.

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Writer: Jayson Mikael