We all know that math and computers are deeply connected. The things that bring entertainment, communication, and information into our homes and fingertips are in their most basic form, numbers. So to truly understand computers and the science that goes into making them work, we must first understand the math which makes up their anatomy.

One of the mathematical programs we use every day is GPS systems such as Google Maps!. They work on several complex applications at once weighing one route against another to find you the fastest one. Factors such as location data, historical traffic patterns, and other metrics are the numbers that make these equations. The software used in Google Maps constantly updates in real-time using machine learning. This way, the app’s suggestions are always the most current, helping you get to your destination as quickly as possible.

It would be impossible to boil down the mathematics of computer science into a single article, but here are a few of the core mathematical mechanics of computer science. Let us take a look at each:

Binary Mathematics:

Binary mathematics is the heart of the computer and an essential math field for computer programming. For all mathematical concepts, the binary number system uses only two digits, 0 and 1. It simplifies the coding process and is essential for low-level instructions used in hardware programming. Computers store data using the binary system. The information we store on computers, from pictures to games and even videos, is stored using the binary number system.

Linear Algebra:

Linear Algebra is the language of machine learning. The heartbeat of the computer is in linear algebra. This branch of mathematics provides concepts crucial to many areas of computer science, including graphics, image processing, cryptography, machine learning, computer vision, optimization, graph algorithms, quantum computation, computational biology, information retrieval and web search. Linear algebra is what makes your video games look so breathtaking, and answers whatever questions you may be asking!

Calculus:

Calculus is a branch of mathematics. It studies the rate at which change occurs. It is often used in computer graphics, scientific computing, problem-solving applications, game programming and computer security.

Calculus is the examination of continuous change and the rate change occurs. It is used in an array of computer science areas, including creating graphs or visuals, simulations, problem-solving applications, coding in applications, creating statistic solvers, and the design and analysis of algorithms. There are two different types of calculus: integral calculus and differential calculus. Together, these disciplines help you to figure out the rate of change, which is an important ingredient in many algorithms and programs.

Differential equations are particularly important. A differential equation calculates how something changes and how fast that happens, so a computer can predict future outputs

Discrete mathematics:

This mathematical discipline is the backbone of Computer Science. Discrete mathematics studies mathematical structures. Its nature is distinct and separable, covering logic, probability, combinatorics, trees, set theory, algorithms, and graphs. It is also called Decision Mathematics or finite mathematics sometimes, it works with the objects that can have distinct separate values. It is accounted as a very effective approach for developing and problem-solving strength.

Statistics:

This branch of mathematics is used for several things, including data mining, data compression, image analysis, and artificial intelligence. Statistics have been especially useful in speech recognition software like Apple’s Siri. Upon receiving your request, Siri records the frequencies and sound waves from your voice and translates them into a code. Siri then breaks down the code to identify particular patterns, phrases, and keywords. Statistics also back programs such as Google Translate, which uses data to perform online translations. Statistics help computers process massive amounts of information in the blink of an eye. You can thank statistics for revolutionizing the way we use computers!

There is a strong link found between computer science and math. It teaches programmers to use abstract language, work with algorithms, self-analyze their computational thinking, and accurately model real-world solutions. Maybe your student will be the next innovative programmer!

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