Computer science is a field that frequently relies on math. But do you have to be a mathematical wiz in order to be successful as a programmer? How much math do you need for computer science?
In this blog post, we will answer these questions and provide resources for learning the necessary math skills for pursuing a career in computer science.
Math as a discipline
Math is the study of quantity, structure, space, and change. It is one of the oldest and most fundamental disciplines.
Computer science relies heavily on math concepts and skills. In order to be successful in computer science, you need to be comfortable performing basic mathematical manipulations, as well as algebra, geometry, and trigonometry. You are also often required to be able to solve equations and understand complex concepts such as probability and statistics.
While you don’t need to be a math genius to pursue a career in computer science, it is important to have a strong foundation in math.
Do you need math for computer science?
While you don’t need to be a math wizard or a mathematician to be a successful software developer, you need to be comfortable applying mathematical logic and problem-solving in order to complete daily programming tasks.
The degree to which math is needed in computer science varies according to the specialization of the software engineer. For example, those who specialize in data science or machine learning will need to be more proficient in advanced mathematical concepts than those who specialize in web development or mobile app development.
That being said, all computer science students should expect to take several math courses as part of their degree program. These courses will provide the necessary foundation for understanding the complex concepts, such as data structures and algorithms, that are introduced in computer science classes.
Why do you need math for computer science?
Math is a critical tool for computer science because it provides the underlying structure for understanding and analyzing algorithms. Algorithms are the basic building blocks of computer programs, so a strong math foundation is essential for anyone hoping to fully understand advanced topics in computer science.
In addition, math is necessary for understanding and working with data structures, which are essential for storing and manipulating data in memory. Finally, math is also used extensively in cryptography, which is the study of secure communication.
Some specific examples of when mathematical concepts are needed to solve computer science problems include:
- Finding the shortest path between two points (known as the “traveling salesman problem”)
- Determining whether a graph is planar
- Encrypting and decrypting data
- Compressing data to save space
- Calculating the probability of an event occurring
These are just a few examples – in reality, math is used in some way, large or small, in most computer science problems. So if you’re interested in pursuing a career in computer science, it’s important to try and acquire at least a basic foundation in math.
What math do you need for computer science?
There are several things that determine what math is needed for computer science, including the specific subfield you plan to specialize in. The most common math concepts and math courses needed for computer science are:
- Binary and hexadecimal systems: Binary and hexadecimal systems are used to represent numbers in computer science. They are used for tasks such as data storage or database design.
- Number theory: Number theory is the study of the properties of numbers. It is used in computer science for tasks such as cryptography or data compression.
- Boolean logic: Boolean logic is the study of the logical operations AND, OR, and NOT. It is used in computer science for tasks such as circuit design or database query optimization.
- Algebra: Algebra is a branch of mathematics that deals with the manipulation of equations and variables. It is used to solve problems in computer science, such as finding the shortest path between two points or determining the amount of data that can be stored on a disk.
- Geometry: Geometry is the study of shapes and spatial relationships. It is used in computer science for problems such as image processing or 3D modeling.
- Trigonometry: Trigonometry is the study of triangles and their angles. It is used in computer science for tasks such as determining the position of objects in a three-dimensional space.
- Probability and Statistics: Probability and statistics are used in computer science for tasks such as analyzing data sets or predicting the outcomes of events.
- Calculus: Calculus is a branch of mathematics that deals with the study of change. It is used in computer science for tasks such as optimizing code or determining the properties of algorithms.
- Linear algebra: Linear algebra is the study of mathematical problems that can be represented in the form of linear equations. It is used in computer science for tasks such as machine learning or data mining.
- Discrete math: Discrete math is the study of mathematical problems that are discrete in nature, meaning they are not continuous. It is used in computer science for tasks such as combinatorics or error-correcting codes.
- Graph theory: Graph theory is the study of graphs and their properties. It is used in computer science for tasks such as network analysis or data visualization.
If this sounds like a lot of math and causes your head to start spinning already, you should try not to worry. After all, you have probably covered more than half of these topics in high school. The remaining courses, which include advanced calculus, linear algebra, discrete math, and graph theory, are usually covered as part of the computer science curriculum in college.
Is math needed for computer science difficult?
Math courses needed for computer science can be quite complicated and are often referred to as the most difficult courses in the computer science curriculum. However, taking concepts one at a time and solving plenty of problems tends help most students pass their exams.
It is important to keep up with the homework assignments and not have any overdue tasks in order to stay in touch with the latest material covered in class.
The most important advice we can give you with regards to tackling your math courses in college is:
- Study in groups. Most instructors allow you to form a team with your classmates to work collectively on your homework assignments. This will help you fill in the gaps of concepts you didn’t fully understand in class or tasks that you can’t quite crack on your own.
- Don’t be afraid to ask for help when you need it. Your professors and teaching assistants are there to help you understand the material.
- Do your homework and practice problems on a regular basis. This will help you stay sharp and catch any concepts that you might have missed in class.
- Stay organized and keep track of what topics you have covered and which ones you still need to review. This will come in handy when you have to study for exams.
- Don’t be discouraged if you don’t understand something the first time around. Math is a cumulative subject, which means that each concept builds on the ones that came before it. If you keep at it and review regularly, you will eventually get it!
Should I study computer science if I am bad at math?
If you are truly passionate about computer science and are capable in other aspects related to this field, you should absolutely study computer science even if you think you are bad at math. The truth is, math is a subject almost anyone can tackle with enough practice and determination.
It is possible you didn’t have an inspiring instructor in the past, which made you believe you are not good enough at math, or a general dislike towards a math class. Things could change in college, so you should give it another try. And even if you don’t excel at math, you can still be an amazing engineer who deals with programming aspects that are only vaguely related to math, such as web development.
Where can I learn math needed for computer science?
If you are not confident in your math skills, there are many resources available to help you improve. These include online resources, books, community college classes, or your CS university program.
The Khan Academy is a non-profit organization that offers free online courses in math and other subjects. They have a section of their website dedicated to math for computer science that covers all of the topics you need to know.
Codecademy is another great resource for learning the basics of computer science. They offer free online courses that cover everything from HTML and CSS to Python and C++. They also have a whole section on different topics in math.
Once you have a strong foundation in math, you can begin to explore more advanced concepts. The book Foundation Mathematics for Computer Science by John Vince is a great resource for learning more about the math needed for computer science. It covers all of the topics you need to know, from basic algebra to calculus and beyond.
If you want to take a more structured and supervised approach, you may take math courses at your local community college. These are convenient and usually very affordable, making them a great choice to attend for any non-degree courses you desire to take.
If you are currently enrolled in a computer science program at a university, the easiest way to give your math skills a level-up may be through your CS curriculum. Take some math courses that you feel could fill in the gaps in your math foundations.
Can I get a job in computer science without math?
Yes, you most certainly can. Many programming tasks don’t require math. In fact, such specializations in computer science as web development, mobile development, and game programming often don’t require much math.
Some of the most difficult and challenging programming topics, such as artificial intelligence or creating algorithms, do require a strong math background. So if you want to specialize in one of these areas, you will need to take some extra math classes.
But overall, computer science is more about logical reasoning and problem-solving than it is about math. So don’t let a fear of math hold you back from pursuing a computer science degree.
What other skills do I need to be successful in computer science?
As we stated before, math is not the only skill that determines your success in computer science. Skills besides math that influence your success as a software engineer include the ability to:
- Think logically and solve problems
- Find creative solutions to difficult problems
- Communicate effectively with others
- Work well in a team environment
- Stay organized and meet deadlines
- Adapt to new technologies and learn new programming languages quickly
Conclusion
Knowledge of math is important in computer science, as it often relies on math for solving programming problems. Several topics, such as binary and hexadecimal systems, calculus, linear algebra, and discrete math are important in computer science.
However, math is not the only determining factor in success of a software engineer. In fact, many programming jobs can be done with minimal math applications.
What do you say, are you ready to tackle the difficulties and get the career of your dreams now that we’ve discussed how much math do you need for computer science? Let’s go get it!
Elmar Mammadov is a software developer, tech startup founder, and computer science career specialist. He is the founder of CS Careerline and a true career changer who has previously pursued careers in medicine and neuroscience.
Due to his interest in programming and years of past personal experience in coding, he decided to break into the tech industry by attending a Master’s in Computer Science for career changers at University of Pennsylvania. Elmar passionately writes and coaches about breaking into the tech industry and computer science in general.
It’s being years since the last time I read such illuminating article on anything !
I fear math since childhood and now after reading this calming a encouraging article, I know I can overcome my fear and enjoy it
Thank you for the detailed and thoughtful article
Thank you for your kind words! Glad the article has been useful to you.