Do You Need to Be Good at Maths for Programming?

Konfinity
November 23,2020 - 5 min read
Do you need to be good at maths for programming?

A lot of people believe that if you’re good in math, you’ll be a good programmer. This statement is neither entirely false nor true. This statement makes its presence too many times and, in this blog, we explain why it misses the mark by a huge margin. On the other hand, a lot of people would say that if you want to be a high-end programmer, maths is a mandatory skill to have. This statement comes from the fact that generally people who know maths like to feel superior to others. In this blog, we would explore the validity of this statement in this blog itself, however, when it comes to programming, it is an ignorance to the diversity of experience and profiles available within the world of programming.

In order to answer the question, ‘Does math make you more smart or intelligent?’, we need to look at the society around us. While a lot of people believes this to be true, they think that being good at math makes one more intelligent. Now, if we go by this rationale, medical doctors, lawyers are ought to be less intelligent because they don’t use math. There are people are extraordinary and do some amazing things in the world but the only thing they don’t know is math. Hence, maths is definitely a valued skill and especially in this capitalistic society we live in, the knowledge of maths might come handy in any profession you choose. However, to regard maths as a barometer of one’s intelligence is an erroneous assumption.

In this blog we discuss, a wide range of topics covering programmers and the maths involved in the world of computing along with the basics required to understand whether you need to be good at maths for programming? Let us begin the blog by first comprehending the nuances of good programming.

Who is a good programmer?

While there is no single accepted definition of a ‘good programmer’, here is a description that encapsulates some of the major skills of a ‘good programmer’. A good programmer is familiar with a range of languages, tools, and best practices and is efficient enough to solve today’s pressing problems in the best possible way and is passionate about learning new things. It is also important that the programmer uses the right language and tool for the given problem. The solution should also be able to write clean and maintainable code that other coders can understand. Testing is also very crucial in the process of development. At the end, there has to be a balance of performance, scalability, security and maintainability. Apart from the technical skills, a programmer has to be a good team player and communicator also.

Now that was a thorough description of a good programmer, but there was no mention of the word ‘maths’ in it. This description may prove useful to understand that maths is not very essential when it comes to programming. However, there is a certain amount of maths involved in programming. Let us look at some of the maths involved in the computing and programming.

When learning maths at schools and universities, it’s majorly all about memorizing a lot of formulas while it is proved that none of that really teaches you how to be a good programmer. It is observed that math does help develop good problem-solving and analytical skills. I don’t disagree with that. However, it is also proved that the human brain is way more intricate than what we understand, and math is not the only way to develop analytical skills. On the other hand, if someone knows how to solve complex math problems, it doesn’t mean they know how to solve a programming problem with clean, maintainable code and deliver working software on time and hence be a good programmer.

Programming in the old days started with 0s and 1s. The assembly language came out after several years, allowed us to write programs in an easier way than using a bunch of 0s and 1s. Then came the language ‘C’ which added a layer of abstraction over the Assembly language. The very base of programming is 0s, 1s, and logical circuits, but now that programming languages have evolved one doesn’t have to know all of that to be a good programmer today. In modern day programming, we are coding at a higher level of abstraction and hence maths is no longer an essential skill in order to become a good programmer. However, there are a few mathematical concepts that need to be learnt in order to solve complex programming problems. In our next section, we discuss the math concepts that every programmer must learn.

Maths for Programming

If you think that programming is all about dealing with numbers and building logic around them and mathematics is one of the most important tools for programmers to develop high- level and complex applications, then we present to you a list of mathematical topics that are most important in the world of programming.

We discussed above that maths is not really an essential skill, however, it is important for all programmers to be well versed with certain topics that are central to programming. Let us now understand some of such topics that you might want to learn if you want to become a programmer.

  1. Graph Theory

    Graph Theory is an important tool in programming only because of its numerous applications. Google maps is one of the most popular application of Graphs. Google maps is basically a giant graph and when you navigate from location A to location B, the underlying algorithms that calculate the shortest distance are backed by various theorems and proofs of graph theory like Dijkstra’s algorithm, Depth First Search, Breadth First Search etc.

  2. Boolean Algebra

    Boolean Algebra is used in the most basic programming. Various logics of Boolean Algebra like AND, OR, NOT, XOR & XNOR are at the heart of understanding the basic computer programming.

    While graph theory and Boolean algebra, there are some concepts which are especially important when you are studying or learning about or working with machine learning or Data Science. For example, Matrices is one of the most important domains of mathematics for Data Scientists. Programmers working with data should be thorough with various terms like matrix, vector, identity matrix, transpose, inverse of a matrix etc. because matrices are widely use to represent data in any Data Science problem. Calculus is another important part of machine learning as it helps in optimizing the cost function using multivariate calculus. It is also extensively used in simulation-based programs where various objects interact with each other which is backed by heavy mathematics.

Another skill important programming is to calculate the performance complexity of an algorithm. One doesn’t need to know how to solve a logarithm problem. However, in order to understand the performance complexity of an algorithm, only the the difference between a linear and logarithmic curve is to be understood.

Hence, programming and mathematics go hand-in-hand and at the very core of it, every programming problem is an underlying mathematics problem where programming has been used simply as a tool to perform computation and obtain the output. Therefore, programmers who aim to be successful should be well-versed in the topics mentioned above. However, it is also true that not every kind of programmer today needs to be great at math. It is just to say that math is great, but it is not an essential skill for the modern- day programmer, it’s more important for a successful programmer to be good at one or two computing languages, data structures, design patterns and databases.

Skills of a Programmer

This is the typical stack of knowledge that programmers need to have in order to make a mark in the IT industry. However, there are some specialised skills also that are required for certain kind of developers. For example, front- end developer are developers who focus on the front end of the website and here is the compilation of skills required to become a front- end developer. Back- end developers work on the server side and are responsible for the functioning of the website and if you want to become a back- end developer, here are skills you might want to acquire. Full-stack developers, on the other hand, are responsible for a lot of tasks ranging from front- end to back- end. Here is a compilation of full- stack developer skills.

There are so many other profiles in the world of programming, from a software developer to mobile application developer, the industry is full of varied profiles. Other than the various roles of a programmer, there are a plethora of computing languages that a programmer can choose. Here is a compilation of best programming languages that you can learn in 2020.

You would observe that in these all compilations of skills, there is no mention of math as an essential skill. Coming to basic programming the general questions are finding the first non-repeating character in a string or finding the kth smallest element in an array. It is essential and more effective for a programmer to know how to solve these programming problems than calculating the intersection of a cube or a sphere.

Conclusion

The bottom line is that maths is important but not essential for programming. There are some concepts of mathematics enlisted in this blog itself that are essential in order to become an ace programmer. If you think we have missed on some of the most important points in order to understand the topic, please feel free for a fruitful discussion with us. We would like to have a conversation with tech enthusiasts like you.

While maths is not an essential skill, there are some pertinent skills that a programmer ought to have apart from industry- level projects. A professional guidance is very important to chalk out a successful career in web development. If you have the zest to become a web developer, we have some good news for you.

Konfinity ‘s Web Development Course is the good news, we were talking about. This course is developed by experts from IIT DELHI in collaboration with tech companies like Google, Amazon and Microsoft and is trusted by students and graduates from IIT, DTU, NIT, Amity, DU and more.

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