Programming is one of the fastest-growing areas in the business world. Companies envision an ever-growing demand for programmers worldwide. It is an excellent choice for any student or professional looking for a career with a great future.
Understanding mathematical operations, arithmetic, calculus, the order of precedence of operations, real numbers, and matrix algebra are the underpinnings of much programming.
Of course, knowing how to operate with numbers in everyday life is a skill we all need. But it is key to understand the meaning of these operations: multiplication, division, and power. A fundamental understanding of them trains your brain to solve problems, which is the main activity in programming. Everything else is around this.
On the other hand, being proficient in probability and statistics is very valuable when it comes to solving problems and, above all, unraveling them practically; and several areas of computer science base their results and processes on these two subjects.
Discrete mathematics also makes up a structural part of programming, and logic is one of its fields of study. It focuses on studying the reasoning and especially if the reason is correct. To achieve this, logic analyzes propositions (or statements) and their relationships. A proposition is a statement that says something that can be true or false. In mathematics, it is said to have a truth value.
Two propositions can be related by means of a connector (in electronics: logic gates, in programming, they are Boolean operators). The best-known connectors are ‘or’ (o) and ‘and’ (y). This gives rise to both mathematical and practical demonstrations. In systems development, they can be used to prove that your algorithm or solution is correct and that it will work with the proposed input data that meets the truth values.
So, are they necessary for programming? Demonstrations are not entirely, but they will be helpful if you want to create proofs that an algorithm works, avoiding the need for thousands of examples to convince someone. Although it is essential to be aware of the operation of the logical connectors, no program escapes from them.
Other areas of study of mathematics, such as sets and numerical systems, are of utmost importance in terms of development. To program, it is very convenient for a basic understanding of how a number system is defined and to know at least four (decimal, binary, hexagonal, or octal).
More advanced math is used in many other programming areas, especially recently becoming increasingly popular: data analysis, blockchain, machine learning, and artificial intelligence. For example, suppose you want to fully understand these matters and other areas of systems development. In that case, extensive knowledge in some of the following subjects is vital: probability and advanced statistics, linear algebra, and differential equations, which require prior knowledge of other mathematical fields.
The most basic observation from where we depart is that programs and software systems, in general, are mathematical objects. This is a matter of fact. The task of programming is the activity of constructing these mathematical objects that satisfy certain requirements, using specific languages, tools, and more.
Math can be intimidating because some of it is abstract. Nonetheless, it is fundamental to remember, as, in any well-written software, the abstraction is introduced for a reason: It helps you communicate more significant and robust ideas. You’ll open up some exciting possibilities when you grasp these ideas and translate them into code.
