University might not always seem the right route for you, especially if you want to go into cybersecurity. But is university worth it after all?Many people who aim for a career in cybersecurity put in a lot of thought when choosing a university course while they are still at the beginning of the road. It's not easy to chart a new career path, to shape your future and be successful in the job you love. So do you really need a university education to go into cybersecurity? What can you learn that'll come in handy for the future?Start with a question that every student asks at least once in their lives. Will what you learn in school be useful in real life? Someone asking this question may think what they learned in school was actually useless. But cybersecurity professionals are hungry for information. For them, nothing is superfluous.At this stage, students often have another question in mind. Why would, for instance, a differential equations course be useful for you to become a cybersecurity professional?If you want a meaningful answer, consider a computer engineering student (the content of the lessons will be different in each country and even in each educational institution). Let's say this hypothetical student takes the following courses in their first year:If you look at these lectures, you could assume they have little to do with cybersecurity. But is that true?Cybersecurity professionals look for new security vulnerabilities almost every day. The technology they use on the basis of this is, of course, programming languages. Learning the syntax structure of a programming language is not enough. Having the ability to develop non-existent algorithms from scratch allows you to be successful in every computing field, not just cybersecurity.Someone working in cybersecurity uses algorithms both when looking for security vulnerabilities in software and when preparing attack codes to exploit the related vulnerability. That would allow them to be part of either a red or blue team, or both.Consider basic penetration testing tutorials you can find anywhere. It is possible to carry out techniques such as an SQL injection with a few simple tools. But to understand the basics of this, of how things actually happen, you will need knowledge of algorithms; for example, a very basic algorithm such as binary search has been used by cybersecurity professionals for years.Mathematics is always core to an education. But to better understand what math has to do with a career in programming, approach these lessons from a cybersecurity perspective.Imagine you found a cybersecurity job and your employer gave you thousands of log files. Your task is "simple": you need to analyze which ones are cyberattacks and which ones are normal user traffic. If you can’t make use of math algorithms, it can take days to check all these logs.You might work on applications that ensure the security of a database containing the data of hundreds of thousands of users, and sometimes the security of money transfers of millions of users too. You will need mathematical algorithms to examine, list, and analyze so much data.If you have an academic career goal in cybersecurity, these numerical courses are your best friend. Even if you are not aiming for an academic career, knowledge of mathematics will make you stand out in every career path. Moreover, fields such as data science, machine learning, and deep learning are merging with cybersecurity already.If you want to work in cybersecurity, you'll gravitate towards courses directly related to it. But knowing data structures, how computers work, and the relationship between hardware and software is absolutely essential for you. Because you will always have to deal with structures on issues such as changing the data that applications keep on their address spaces, memory overflow vulnerabilities, and exploiting these vulnerabilities.It is essential that you have a command of concepts such as heap, stack, and linked list, especially for reverse engineering. Do you really need to know all this? That depends on how specialist you want to be in cybersecurity. There are many who use ready-made tools and are not especially interested in stretching themselves more. In order to get ahead and become sought-after, don't underestimate this knowledge.On the other hand, it is not possible to become an expert in penetration testing without knowing the world of a software developer. A cybersecurity engineer should be able to think like a software developer and understand their aims. For example, if you examine PHP Object Injection vulnerabilities, you will see how useful object-oriented programming can be.All of these are proof that the courses taken at university are necessary. You can turn any lessons to your favor.It really helps if you are a bookworm. You may be working for a company that uses only Python and JavaScript libraries, but that's no reason not to learn technologies like C# and .NET. Of course, it is not possible to learn all tech, frameworks, and programming languages. However, learning as much as you can will help a lot, especially in penetration tests.You never know when this will work for you. Your greatest weapon is your curiosity. Try to consume every academic article, research paper, experiment result, and book you can. You will realize how far you have come in a much shorter time than you thought. You should spend more than half of your free-time reading and researching, because there are so many things to learn and try. Never lose your curiosity.It is not possible to be an expert in every field of cybersecurity, but there are lots of different areas to specialize in. Nonetheless, it is important to have a basic knowledge of all fields, so even basic research will help. Later on, you will be able to learn for yourself which field you want to work in and have the opportunity to choose the field in which you will specialize.An engineer and software developer who is a fan of math and technology. He has always liked computers, mathematics and physics. He has developed game engine projects as well as machine learning, artificial neural networks and linear algebra libraries. Moreover continues to work on machine learning and linear matrices.