Most of the modern world – work, private life, and entertainment – revolves around computers and IT in general. Naturally, this landscape creates a high demand for computer science jobs. As a result, BSc Computer Science positions are well-paid and offer excellent career opportunities.

With all these advantages considered, it’s no wonder that people from other professions pivot toward computer science. This includes biology students, too.

But can a biology student do BSc Computer Science? And, equally as important, should they?

The answer to the first question is relatively complex and will represent the bulk of this article. But the second answer is a resounding yes. Interdisciplinary education can be a massive advantage in today’s world, providing venues for innovation and greater career advances.

Let’s delve deeper into the question of can a biology student do BSc Computer Science.

Background on BSc Computer Science

A BSc degree is often a part of professional development for people interested in IT. The degree usually follows a core computer science course. After obtaining the BSc, you can move forward towards a specialization or pursue a PhD in the field.

As a biology student, your path to BSc Computer Science will be different. The first step on the way is to understand what computer science is, which areas it covers, and what core skills it requires. This section will explain just that, plus the career opportunities that come with BSc Computer Science.

Definition and Scope

Computer science deals with computer systems. If you’re (rightfully) wondering what that means precisely, the answer is: practically anything related to computers.

A computer scientist can work on the architecture and structure of a processor chip. On the other hand, their colleague could be engaged in supporting the structure of the internet. Both roles fall under the umbrella of computer science.

At its core, this branch of IT concerns with questions about the nature of computing. In that light, one of the computer scientist’s main tasks is to understand what a computer system is. Then, these professionals can move onto designing different systems for particular purposes.

Core Subjects and Skills

BSc Computer Science courses teach core subjects that provide the essential skills for the job. As you might presume, programming is the crucial skill of a computer scientist. This skill requires proficiency in programming languages and a deep understanding of data structures. In addition, knowing the ins and outs of algorithms is pivotal for programming.

Software development is another skill that computer scientists must have. Besides coding knowledge, this skill calls for high proficiency in the principles of software engineering. A good computer scientists should be able to perform the entire development process from coding to implementation.

Computer science calls for a good understanding of math basics like algebra and calculus. However, advanced techniques will also be necessary.

Finally, a computer scientist should have a firm grasp on data analysis and visualization. The former improves professional capabilities, while the latter helps communicate the data to the stakeholders.

Core subjects in BSc Computer Science courses that tackle these and other skills include:

• Programming principles
• Computer networks
• Computer architectures
• Foundational mathematics
• Data structures and Algorithms
• Web development
• Introduction to operating systems
• Cloud computing
• Programming paradigms

Job Prospects and Career Opportunities

Employment in the computer science sector is growing rapidly, following a trend that’s projected to continue throughout the decade. The U.S. Bureau of Labor Statistics expects a 15% growth in the computer science landscape, along with hundreds of thousands of new jobs.

As the IT sector keeps innovating, even more jobs may become available. After all, many of today’s most desired professions didn’t exist at the start of the century, and computer science is developing rapidly.

Some of the career opportunities in computer science are for programmers, systems analysts, support specialists, software and computer engineers, and data scientists.

Comparing Biology and Computer Science

The question of can a biology student do BSc Computer Science comes down to a few crucial considerations. One of the first things you might ask is: what do computer science and biology even have in common.

Surprisingly, there are considerable similarities between the two fields.

Similarities

The most obvious aspect that computer science and biology share is that both are scientific disciplines. This means that the scientific approach is a hard requirement for both fields.

Biology and computer science aim to solve problems following two crucial methods: data analysis and interpretation and the scientific principle. A computer scientist will follow the same path to a conclusion as a biologist:

• Observation
• Question
• Hypothesis
• Prediction
• Testing
• Iteration

Furthermore, both disciplines will utilize mathematical models, although computer science will lean into math more than biology. Lastly, living organisms can be thought about as systems, which is somewhat similar to a computer scientist’s understanding of computers and other IT technologies.

Differences

Of course, the differences between biology and computer science will be much more evident. The two fields employ completely different sets of skills and require knowledge specific to their subjects. Naturally, people specializing in biology and computer science will also have completely different career paths.

When it comes to the underlying principles behind the two sciences, other crucial differences come to mind:

• Computer scientists regularly build artificial systems while biologists explore natural ones.
• As a science, biology is more based on observation, unlike the often experimental computer science.
• Biology is often regarded as an applied field, while computer science may be viewed as more abstract.

Assessing the Feasibility of a Biology Student Pursuing BSc Computer Science

Now that we’ve seen what makes biology and computer science similar in some regards and different in others, let’s return to the original question:

Can a biology student do BSc Computer Science?

To answer that question, we’ll need to look at two aspects. Firstly, doing a BSc in Computer Science comes with certain prerequisites. And second, you as a biology student must be ready and willing to adapt to the new field.

Analyzing the Prerequisites

The essential skills that are required for a BSc in Computer Science include programming and mathematics. As a biology student, you’ll likely already have some courses in math, which will make that part of the equation easier.

However, programming definitely won’t be a part of the standard biology curriculum. The same goes for other computer science skills.

Yet, this mismatch doesn’t mean that a biology student can’t pivot towards computer science. The process will only require more effort than for someone with a computer science background.

To enroll in a BSc Computer Science program, you’ll need to have a good grasp of the mentioned skills. Since studying biology doesn’t offer knowledge on programming or computer science in general, you’ll need to acquire those skills in addition to your primary studies.

The good news is that you won’t need any other specific knowledge besides math and the basics of programming and computer science. If you’re seriously considering transitioning into computer science, fulfilling these prerequisites will be well worth your while.

Evaluating the Adaptability

Besides the necessary entry-level knowledge for a BSc Computer Science, another factor will determine your success: whether you can adapt to the new field of study.

The similarities between biology and computer science will play a massive role here.

You can lean into your understanding of the scientific principle and apply it to computer systems rather than biological organisms. The transition can be viewed as following the same general methods but using them on a different subject.

Also, data collection and analysis skills will be an excellent foundation for computer science. These skills are vital in biology. Luckily, they also represent an essential part of computer science, so you’ll be able to apply them to the new discipline relatively easy.

Granted, the usefulness of your prior knowledge and skills will reach a limit at a point. Then, you’ll need to show another crucial quality: the willingness to adopt new concepts and learn new subjects.

Your advantage will be in the foundational scientific skills that you’ll have as a biologist. Building on those skills with computer science-specific knowledge will make your transition smoother. The key consideration here will be that you’re ready to learn.

Options for Biology Students to Transition Into BSc Computer Science

The final part of answering the question of can a biology student do BSc Computer Science is the practical method of transitioning. You’ll have several options in that regard:

• Enroll in a bridge course or a preparatory program
• Complete an online course and get the appropriate certification
• Rather than biology alone, opt for an interdisciplinary degree or a dual-degree program
• Pursue a biology degree simultaneously with a computer science minor

Each of these options will help you gain the necessary knowledge for the BSc and prepare for a career in computer science.

Can a Biology Student Do BSc Computer Science? Absolutely!

As you’ve seen, the path from a biology student to BSc in Computer Science isn’t a straight one. However, it’s completely achievable if you have the motivation.

Getting interdisciplinary education will represent an excellent opportunity for professional growth. Better yet, it will open up your possibilities for personal development as well. Learning about a new discipline is always a benefit, even if you pursue a different career path later in life.

If computer science sounds like an interesting prospect, nothing stops you from following that line of study. Fortunately, the opportunities for just that are readily available. Enlist in a quality BSc course and start building your knowledge base and skills.

AI is already a massive industry – valued at $136.55 billion (approx. €124.82 billion) as of 2022 – and it’s only going to get bigger as we come to grips with what AI can do. As a student, you stand on the cusp of the AI tidal wave and you have an opportunity to ride that wave into a decades-long career.

But you need a starting point for that career – a BSc computer science with artificial intelligence. The three courses discussed in this article are the best for budding AI masters.

Factors to Consider When Choosing a BSc Computer Science With AI Program

Before choosing your BSc, you need to know what to look for in a good course:

• Institution Accreditation – Whoever provides the course should offer solid accreditation so that you know you can trust the institution and that potential future employers actually respect the qualification you have on your VC.
• An AI-Focused Curriculum – Not all computer science bachelor’s degrees are the same. The one you choose needs to offer a specific focus on AI or machine learning so you can build the foundations for later specialization.
• Faculty Expertise – A course led by instructors who don’t know much about AI is like the blind leading the blind. Every mentor, instructor, and lecturer needs to have provable knowledge and industry experience.
• Job Opportunities – Every chance you have to “get your hands dirty” with AI is going to look great on your CV. Look for courses that create pathways into internships and job programs. Associations with organizations like IBM are a great place to start.
• Financial Aid – It isn’t cheap to study a BSc artificial intelligence and machine learning. Degrees cost thousands of Euros per year (the average in Europe is about €3,000, though prices can go higher) so the availability of financial aid is a huge help.

Top BSc Computer Science With AI Programs

Studying from the best is how you become a leader in the AI field. The combination of expert tuition and the name recognition that comes from having a degree from one of the following institutions stands you in good stead for success in the AI industry. Here are the top three organizations (with degrees available to overseas students) in the world.

Course 1 – BSc Artificial Intelligence – The University of Edinburgh

Named as one of the top 10 AI courses in the world by Forbes, The University of Edinburgh’s offering has everything you need from a great BSc computer science with artificial intelligence. It’s a four-year full-time course that focuses on the applications of AI in the modern world, with students developing the skills to build intelligent systems capable of making human-like decisions. The course is taught by the university’s School of Informatics, led by National Robotarium academic co-lead Professor Helen Hastie.

The course starts simple, with the first year dedicated to learning the language of computers before the second year introduces students to software development and data science concepts. By the third year, you’ll be digging deep into machine learning and robotics. That year also comes with opportunities to study abroad.

As for career prospects, The University of Edinburgh has a Careers Service department that can put you in line for internships at multi-national businesses. Add to that the university’s huge alumni network (essentially a huge group of professionals willing to help students with their careers) and this is a course that offers a great route into the industry.

Course 2 – Artificial Intelligence Program – Carnegie Mellon University

Ranked as the top university in the world for AI courses by Edurank, Carnegie Mellon University is a tough nut to crack if you want to study its world-renowned program. You’ll face a ton of competition, as evidenced by the university’s 17% acceptance rate, and the program is directed by Reid Simmons. For those who don’t recognize the name, he’s been a frontrunner in leveraging AI for NASA and was the creator of the “Robotceptionist.”

As for the course, it blends foundational mathematical, statistical, and computer science concepts with a wide variety of AI modules. It’s robotics-focused (that’s no surprise given the director), though you’ll also learn how AI applies on a perceptive level. The use of AI in speech processing, search engines, and even photography are just some examples of the concepts this course teaches.

Carnegie Mellon takes an interesting approach to internships, as it offers both career and academic internships. Career internships are what you’d expect – placements with major companies where you get to put your skills into practice. An academic internship is different because you’ll be based in the university and will work alongside its faculty on research projects.

Course 3 – BSc in Artificial Intelligence and Decision Making – Massachusetts Institute of Technology (MIT)

It should come as no surprise that MIT makes it onto the list given the school’s engineering and tech focus. Like Carnegie Mellon’s AI course, it’s tough to get into the MIT course (only a 7% acceptance rate) but simply having MIT on your CV makes you attractive to employers.

The course takes in multiple foundational topics, such as programming in Python and introductions to machine learning algorithms, before moving into a robotics focus in its application modules. But it’s the opportunities for research that make this one stand out. MIT has departments dedicated to the use of AI in society, healthcare, communications, and speech processing, making this course ideal for those who wish to pursue a specialization.

Networking opportunities abound, too. MIT’s AI faculty has 92 members, all with different types of expertise, who can guide you on your path and potentially introduce you to career opportunities. Combine that with the fact you’ll be working with some of the world’s best and brightest and you have a course that’s built for your success in the AI industry.

Emerging BSc Computer Science With AI programs

Given that AI is clearly going to be enormously important to developing industry in the coming years, it’s no surprise that many institutions are creating their own BSc computer science with artificial intelligence courses. In the UK alone, the likes of Queen’s University Belfast and Cardiff University are quickly catching up to The University of Edinburgh, especially in the robotics field.

In North America, the University of Toronto is making waves with a course that’s ranked the best in Canada and fifth in North America by EduRank. Interestingly, that course is a little easier to get into than many comparable North American courses, given its 43% acceptance rate.

Back in the UK, the University of Oxford is also doing well with AI, though its current courses tend to be shorter and specialized in areas like utilizing AI in business. We’re also seeing Asian universities make great progress with their courses, as both Tsinghua University and Nanyang Technological University are establishing themselves as leaders in the space.

Importance of Hands-On Experience and Internships

As important as foundational and theoretical knowledge is, it’s when you get hands-on that you start to understand how much of an impact AI will have on business and society at large. Good universities recognize this and offer hands-on experience (either via research or internship programs) that offer three core benefits:

• Gain Practical Skills – Becoming a walking encyclopedia for the theory of AI is great if you intend on becoming a teacher. But for everybody else, working with hands-on practical experiments and examples is required to develop the practical skills that employers seek.
• Networking – A strong faculty (ideally with industry as well as academic connections) will take you a long way in your BSc computer science with artificial intelligence. The more people you encounter, the more connections you build and the better your prospects are when you complete your course.
• Enhanced Job Prospects – Getting hands-on with real-world examples, and having evidence of that work, shows employers that you know how to use the knowledge you have knocking around your head. The more practical a course gets, the better it enhances your job prospects.

Scholarships and Financial Aid Opportunities

Due to BSc artificial intelligence and machine learning courses being so expensive (remember – an average of €3,000 per year), financial aid is going to be important for many students. In the UK, that aid often comes in the form of student loans, which you don’t have to start repaying until you hit a certain earnings threshold.

When we take things Europe-wide, more scholarship and financial aid programs become available. The Erasmus program offers funding for master’s students (assuming they meet the criteria) and there are several scholarship portals, such as EURAXESS and Scholarshipportal designed to help with financial aid.

If this is something you’re interested in, the following tips may help you obtain funding:

• Excel academically in pre-university studies to demonstrate your potential
• Speak to the finance teams at your university of choice to see what’s currently available
• Apply for as many scholarship and aid programs as you can to boost your chances of success

Try the Top BSc Artificial Intelligence and Machine Learning Programs

The three BSc computer science with artificial intelligence programs discussed in this article are among the best in the world for many reasons. They combine intelligence course focuses with faculty who not only know how to teach AI but have practical experience that helps you learn and can serve useful networking purposes.

The latter will prove increasingly important as the AI industry grows and becomes more competitive. But as with any form of education, your own needs are paramount. Choose the best course for your needs (whether it’s one from this list or an online BSc) and focus your efforts on becoming the best you can be.

Books represent gateways to new worlds, allowing us to gain valuable knowledge on virtually any topic. Those interested in exploring computer science books face two challenges. First, just like you can’t build a good house without a proper foundation, you can’t expand your knowledge if you don’t understand basic concepts. Secondly, technology is always evolving, so besides understanding how things work, you need to stay current with the latest trends.

Finding books that help you build a good foundation and follow innovations isn’t easy. Fortunately, you don’t have to go through hundreds of titles to find the good ones. Here, we’ll introduce you to the best BSc Computer Science books that will set you up for success.

Top BSc Computer Science Books

These BSc Computer Science books can “program” your mind and help you absorb knowledge.

Introduction to Computer Science

Many people are eager to learn how to program and immerse themselves in the IT world. But the first step toward that is adopting fundamentals. Before jumping into the IT industry, you need to learn more about computer science and the basic concepts behind it.

Computer Science Illuminated by Nell Dale and John Lewis

This student-friendly book sheds light on computer science. It explores operating systems, hardware, software, and networks from “neutral ground” (without focusing on particular programming languages). Therefore, if you don’t “speak” programming languages just yet, this book will be your best friend.

Intro to Python for Computer Science and Data Science: Learning to Program With AI, Big Data, and the Cloud by Paul Deitel and Harvey Deitel

If you want to be a programming expert, you may need to speak Python, a universal language with a wide array of applications. This book teaches you how to use Python in computer science and offers the perfect balance between theoretical and practical knowledge. It transforms complex information into comprehensive and engaging data.

Data Structures and Algorithms

Finding the best BSc Computer Science book on data structures and algorithms can feel like trying to find a needle in a haystack. We found the needle for you and offer the best options.

Data Structures and Algorithms Made Easy by Narasimha Karumanchi

This book is a winner in the data structures and algorithms game. It’s the perfect option for beginners interested in learning the topic from scratch and building a solid foundation for more advanced levels. It covers basic concepts and moves on to more complex stuff without overwhelming the readers.

Data Structures and Algorithms in Java by Robert Lafore

If you’re familiar with Java and want to start with data structures and algorithms, this book is the gold standard. It will guide you on a journey from basic Arrays and Strings to advanced structures like Hash-Tables and Graphs.

Computer Networks

Computer networks are grids through which computing devices “talk to” each other and share data. Here are the books you can use to improve your knowledge and get ahead in your career.

Computer Networks by Andrew S. Tanenbaum

If you want to understand the nitty-gritty behind computer networks, this book is the way to go. Hop on a journey through email, the world wide web, video conferencing, and much more, to understand how the networks work and how to use them to your advantage.

Every chapter follows the same, easy-to-follow structure containing basic principles and real-life examples.

Computer Networking: A Top-Down Approach by James F. Kurose and Keith W. Ross

This beginner-friendly book takes a somewhat unusual approach. It first introduces students to applications and uses them to explain fundamental concepts. That way, students are exposed to the “real world” early on and can understand how networking works with ease.

Operating Systems

An operating system for a computer is like oxygen for a human; it can’t live without it. Operating systems are interfaces that support everything computers do. Here are the best books about them.

Operating Systems: Three Easy Pieces by Remzi Arpaci-Dusseau and Andrea Arpaci-Dusseau

How do operating systems work? What are the three basic concepts hiding behind every OS? Find the answers to these questions and learn everything OS-related in this book. While beginner-friendly, this amazing study can be combined with more advanced materials and offer a deeper understanding of modern OSs.

Guide to Operating Systems by Greg Tomsho

This book represents a detailed guide on installing, updating, maintaining, and configuring operating systems and everything related to them. Besides offering general info, the book explores specific OSs and allows you to peek into this world without feeling overwhelmed.

Database Systems

Database systems are like virtual warehouses where you can keep your data secure. They’re the ones we can “thank” for easy information retrieval, browsing, and organization. If you want to learn the ins and outs of database systems, these books can help.

Database Systems: The Complete Book by Hector Garcia-Molina, Jeffrey D. Ullman, and Jennifer Widom

This book is the holy grail for many computer science students. It offers a comprehensive approach and detailed explanations of everything related to database system design, use, and implementation. The book is extensive, but it’s written in an engaging way, so reading through it is a breeze.

Database Systems: Design, Implementation, & Management by Carlos Colonel and Steven Morris

Building your virtual warehouses for storing data may seem impossible. But it can become your reality thanks to this excellent book. It contains clear and comprehensive instructions on building database systems, offers concrete examples, but also focuses on the bigger picture and latest industry trends.

Software Engineering

Designing and constructing software is no walk in the park. If you’re interested in this industry, you need to build your skills meticulously. Books that can help you on this exciting (and sometimes frustrating) journey are reviewed below.

Clean Code: A Handbook of Agile Software Craftsmanship by Robert C. Martin

In this book, Robert C. Martin, a software engineering legend, discusses the seemingly insignificant differences between bad and poorly-written codes. He explains which “symptoms” bad codes manifest and how to clean them.

Code Complete: A Practical Handbook of Software Construction by Steve McConnell

One of the first (and smartest) steps toward building quality code is getting this book. Here, the author summarized everything there is to know about constructing software. Since the book contains both the basics and the more advanced construction practices, everyone finds it useful, both beginners and pros.

Additional Resources for BSc Computer Science Students

BSc Computer Science books aren’t the only spring you should drink water from if you’re thirsty for knowledge on the subject.

Online Platforms and Courses

Online platforms and courses are great resources for those who want to expand their knowledge and learn how to cash it in. The internet is overflowing with great courses focusing on various aspects of computer science. Here are a few ideas to get you started:

• Open Institute of Technology (OPIT) – The institute offers a comprehensive online BSc in Computer Science. Throughout the program, students get acquainted with everything computer science-related. After completing their studies, they’ll be able to land high-paying jobs.

• Udemy and Coursera – Although not “official” institutes and universities, these platforms deserve a seat at the table. Both Udemy and Coursera offer quality computer science courses held by some of the most respected names in the industry.

Coding Practice Websites

You’ve read books, attended courses, and feel like you know everything there is to know about the theoretical part. But is there a way to put this theory into practice and see whether your codes work? The answer is yes! Practice makes perfect, and coding practice websites will become your best friends and help you conquer programming.

• Coderbyte – Solve real-life coding issues and drive your skills to perfection. With over a dozen available programming languages, you can try out as many ideas as you’d like.
• HackerRank – HackerRank is home to hundreds of coding challenges. Plus, it has leaderboards, so you can see how you compare to other coders. It’s also home to useful tutorials, and since the website is popular, you may even be able to land your dream job.

Computer Science Forums and Communities

Is there a better place for like-minded people to meet and discuss the topics they’re passionate about? Computer science forums and communities should be an important stop on your way to becoming an expert on the subject.

Tips for Success in BSc Computer Science

Success doesn’t happen overnight (at least for most people). If computer science is your true passion, here’s how to master it:

• Focus on the basics to create a good foundation.
• Put your thinking cap on and practice problem-solving and critical thinking skills.
• Participate in group projects and collaborations (teamwork makes the dream work).
• Keep up with the latest industry trends.
• Gain valuable hands-on experience through internships.

Acquire Computer Science Knowledge Effectively

Although books don’t offer practical knowledge, they can be invaluable allies in setting a great theoretical foundation. By carefully choosing the best books and putting effort into developing your skills, you’ll become a pro in a jiff.

Computers are already ubiquitous in the workplace, with the constantly-evolving concept of cloud computing becoming so popular that Tech Jury says 90% of businesses were in the cloud (in some form) in 2022. All of those systems need maintenance and software, requiring people who are dab-hands with keyboards at their fingertips to build networks, analyze data, and develop software.

Enter computer scientists.

By studying computer science, you open yourself up to a branching career path that could take you into almost any sort of business. But before that, you need to know the answer to a simple question – “Is BSc Computer Science a good course?”

Understanding BSc Computer Science

Think of a BSc in Computer Science as though it’s a buffet, with every topic covered being a different dish. You’ll get a taste of everything that’s on offer in the computing field, with your later educational (and career) decisions being based on the dish (i.e., the topic) that you like best. Among those topics and study areas are the following:

• Networks and Computer Systems – Taking a more hardware-oriented focus (though software plays a part), this topic covers how to connect computers so they can interact with one another.
• Programming – The language of computers is one you’ll need to learn how to speak if you want to develop software or websites. You’ll discover that there are a lot of languages to choose from, each with its own specific uses.
• Artificial Intelligence (AI) – As one of the fastest-growing fields in computing (Statista anticipates growth from $100 billion in 2021 to almost $2 trillion by 2030), AI is already becoming essential in business. You’ll learn the concepts that govern AI, such as machine learning and neural networks.
• Network Security – Every advancement in computer science brings with it malicious parties who wish to use (or subvert) that advancement to their own ends. Computer science courses teach the foundational aspects of network security, setting the stage for later specialization.

Moving beyond what you study (and the above isn’t an exhaustive list of topics), how long you spend on earning your BSc in Computer Science is another key deciding factor. Most traditional universities offer three-year courses, extending to four years if you take an internship or in-course work. The newer breed of online universities offer more flexibility, with some fast-track courses taking as little as two years, while others offer a more free-form version of study that lets you move at your own pace. With the latter, you could take several more years to complete your degree, though you’ll be able to fit your studies around work and family more easily than you would with a full-time course.

Benefits of BSc Computer Science

Assuming you’re willing to place the time (and monetary) investment into a BSc in Computer Science, there are three core benefits you’ll get from the course.

1 – Acquire In-Demand Skills and Knowledge

The basics you learn are in demand in most companies, with many offering additional training and tuition to help you build beyond the basics to become a specialist. Key areas of interest for employers include:

• Programming – Those who can speak the language that lies behind software are always in demand, with programmers earning an average hourly rate of $33.10, according to Indeed. Salary expectations climb as you move through the ranks, with senior software engineers capable of earning in the early six figures.
• Data Structures and Algorithms – Problem solvers are popular in any business. The knowledge of algorithms you develop when studying computer science allows you to create code (almost like a set of steps) that’s designed to solve problems. The same applies to data structures, which focus on the locations and methods used to keep data organized.
• Computer Networks and Security – Even a small office has a network of computers, laptops, smart devices, printers, and servers that all need to communicate with one another. Computer scientists enable that communication, and keep the “conversations” machines have with each other shielded from intruding eyes.

2 – Versatility and Adaptability in the Job Market

Computer science graduates are like the chameleons of the job market. They have so much foundational knowledge in an array of subjects that they’re well-placed to be “Jacks of all trades” as general computer experts. Plus, the base they have can be built from, setting the stage for them to specialize in specific areas of computing based on their preferences.

We’ll dig into some specific roles you could take (along with their salaries) in the next section of the article.

3 – Opportunities for Further Education and Specialization

You’re already part way down the road to computer science mastery once you have your BSc, so why stop there? The opportunity exists for further education and specialization, which could open the door to further career opportunities:

• Masters and Ph.D. Programs – A Master’s degree in computer science (or a related subject) is the next logical educational step once you have your BSc. You’ll build on what you’ve already learned, in addition to having a chance to specialize in your thesis. PhD programs aren’t immediately open (you’ll need your Master’s first) but they give you a chance to delve into subject-specific research and could set you up for a career in teaching computer science.
• Professional Certifications – If you prefer the less formal educational route, professional certifications enable you to study at your own pace and give you handy pieces of paper you can use to prove your skills. Great examples include Cisco’s CCIE program and CompTIA’s range of certifications.

Job Prospects and Career Opportunities

Building on the previous mention about your chameleon-like ability to get jobs in multiple fields, you need to know is BSc in Computer Science good for the career-focused student. These are the roles you can get (with salary data from Indeed).

Software Development and Engineering

Rather than being the person who uses software, you can be the person who forms and puts together the building blocks that make the software tick. Software developers and engineers use their coding skills to create the next great apps, websites, computer games, and anything else that needs a computer or mobile device to run.

Average Salary – $114,470

Data Analysis and Data Science

Data, data everywhere, and not a drop to drink. That little spin on the classic “lost at sea” phrase tells you everything you need to know about how many companies feel in the Big Data world. They’re collecting tons of data but don’t know how to organize what they have or extract useful information from it. Data analysts and scientists solve that problem.

Average Salary (Data Analyst) – $74,570

Average Salary (Data Scientist) – $129,574

Cybersecurity and Network Administration

There’s a never-ending battle being waged between network administrators and hackers, with each trying to stay one step ahead of the other. Cyberattacks are on the rise, with Security Magazine pointing out that attacks around the globe increased by 38% in 2022. That means there’s always demand for cybersecurity specialists.

Average Salary – $107,063

Research and Academia

Rather than using your skills to benefit private enterprises, you could be responsible for the next generation of computer scientists. The academic path is a noble one, though not always the most profitable, and it affords you the chance to research the subjects you’re passionate about. The level you reach in academia depends on your own academic accomplishments, with a BSc usually being enough for school-level teaching. You’ll need a Master’s or Ph.D. to go into further education or complex research.

Average Salary (Computing Teacher) – $26.79 per hour

Entrepreneurship and Freelance Opportunities

Why restrict yourself to a single company when you could build your own or spread your scientific seeds wide by becoming a freelancer? More control over your destiny is the biggest benefit of this career path, though there’s a more “sink or swim” mentality. Those who hit it big with a great business idea can hit it really big, but there are plenty of failed computing businesses on the entrepreneurial road.

Average Salary – It all depends on what you do and how well you do it

Factors to Consider When Evaluating the Worth of BSc Computer Science

If you’re still asking “Is BSc Computer Science a good course?” the answer is a definite “yes.” But there are some factors to consider before you commit to several years of computing studies:

• Personal Interests and Aptitude – Success in any area of study requires a passion for your subject and a certain amount of talent in the field. If you’re missing one (or both) of these for computer science then a BSc may not be for you.
• Job Market Trends – It’s very possible to make a six-figure salary as a computer scientist, though specialization is often needed to hit the highest figures. Still, it’s worth keeping an eye on what’s happening with the job market to ensure you’re studying toward a future role.
• Return on Investment – Undergraduate programs can cost anywhere between $15,000 and $85,000, so you need to feel confident that a computer science course is the right one for your future career. Otherwise, you’re left with a massive hole in your bank balance that you need to fill with student loan repayments.
• Job Satisfaction – Working yourself into the ground is never a good thing. You need to feel confident that you’ll achieve the appropriate balance between your work, personal, and family lives.

Comparing BSc Computer Science With Other Courses

A BSc in Computer Science is far from your only choice if you’re interested in delving into computers. Here are three alternatives to consider.

BSc Information Technology

Though an IT degree covers some of the same ground as a computer science one (especially when it comes to computer networks), you’ll trade theoretical knowledge for practical application. Expect to do a lot of work with databases and basic software, with some coding along the way.

BSc Data Science

As a more specialized course, a BSc in Data Science sees you delving deeper into the math and statistics behind computational systems. You’ll learn how to analyze data and may get a better grip on emerging tech, such as machine learning, than you would with a computer science degree.

Bachelor of Engineering (Computer Science)

A bachelor of engineering takes a more hardware-centric focus than a BSc, with this course teaching more about the principles of electrical engineering and how our computing devices actually work. There are still software components, and you’ll touch on similar subjects to a BSc, but you’ll get more practical experience with this course.

Is a BSc in Computer Science Good for You?

The most important question to ask isn’t “Is BSc Computer Science a good course,” but rather is it the right course for you? Your career goals, coupled with your desire (or lack thereof) to invest your time and money into the degree, may be the main deciding factors.

As with any course, ask yourself what the ultimate benefit is to you and weigh up your options (remembering that there are several types of computing degrees) to make the right choice.

Few computer science concepts have been as popular as artificial intelligence and machine learning. Traditionally reserved for sci-fi and fantasy, these disciplines have entered the real world and been eagerly welcomed by the public. Of course, tech companies and businesses across all industries were also quick to reap the benefits of AI and ML.

Today, the job market is full of offers for experts in the two fields. More importantly, plenty of those job listings come from leading companies, representing prime career opportunities. But tech giants want genuine experts – people thoroughly educated in the field.

Getting an MSc in AI and machine learning is an excellent way to gain the knowledge, experience, and proper credentials to land some of the most profitable and exciting jobs in the industry. The possibilities here are almost unlimited: You can enroll at a university for live classes or obtain your master’s degree in AI and machine learning online.

We’ve compiled a list of the best programs to get your masters in AI and ML. Let’s look at what the top educational institutions have to offer.

Factors to Consider when Choosing a Masters Program in AI and ML

Picking the best masters in machine learning and artificial intelligence isn’t a straightforward choice. Many institutions offer courses on the subject, but not all of them are of equal quality. Here are the essential criteria to consider when deciding which course to take:

• University reputation and ranking: The first factor to look at is whether the university is well-regarded among current and former students, as well as internationally. A reputable institution will usually meet other quality criteria as well.
• Curriculum and course offerings: Every masters in AI and ML program will be slightly different. You should examine the curriculum closely to find out if the classes match your educational and professional goals.
• Research opportunities and faculty expertise: There’s plenty of theory in AI and ML, but the core value of these disciplines lies in practical application. That’s why you’ll want to pick a program with ample research and hands-on opportunities. On a similar note, the faculty members should be industry experts who can explain and show real-life uses of the skills taught.
• Job placement and industry connections: Besides the knowledge, top MSc in AI and machine learning programs will provide access to industry networks and the relevant job market. This will be one of the greatest advantages of enrollment. You’ll get the chance to enter the AI and MS professional landscape upon graduation or, in some cases, during the program.
• Tuition fees and financial aid: Studying at top universities can be costly and may impact your budget severely. However, that doesn’t mean you can’t get quality education without breaking the bank. You can find reasonably priced offers or financial aid methods to help you along the way.

Top 5 Masters Programs in AI and ML

1. Imperial College London – MSc in Artificial Intelligence

The Imperial College in London offers intensive AI and programming training in this MSc program. During your studies, you’ll gain the essential and advanced technical skills, as well as experience in practical AI application.

This program lasts for one year and includes full-time studying on site in South Kensington. The total fee, expressed in British Pounds, is £21,000 for UK students and £39,400 for learners from abroad. To enroll, you’ll need to meet the minimum requirements of a degree in engineering, physics, mathematics, or similar fields.

In terms of the curriculum, this program’s core modules include Introduction to Machine Learning, Introduction to Symbolic Artificial Intelligence, and Python Programming. You’ll participate in individual and group projects and have access to state-of-the-art computing labs.

Certain projects are done in collaboration with leading AI companies, representing an excellent opportunity to get in touch with acclaimed tech professionals. As a result, graduates from this program have improved chances of finding high-level work in the industry.

2. University of Tuebingen – International Master’s Program in Machine Learning

The master’s in machine learning from the University of Tuebingen is a flexible program with particular emphasis on statistical ML and deep learning. The institution ensures the lectures follow the latest trends in the ever-developing machine learning field.

You can finish the studies during the four semesters of the program or take an extra semester. In that case, you’ll be eligible for a note of distinction, depending on the quality of your thesis. Non-EU students will need to pay a fee of €1,500 per semester along with a €160 semester fee. Students from the EU and others eligible for fee exceptions will only have to cover the semester fees.

As mentioned, the curriculum is exceptionally flexible. The program features only three mandatory lectures: Probabilistic Inference and Learning, Statistical Machine Learning, and Deep Learning. All other lectures are elective, so you can tailor the program to fit your needs and goals precisely.

The lecturers at Tuebingen University, all renowned machine learning researchers, will work with you actively during the program. Owing to the institution’s interdisciplinary approach, you’ll be able to work on your thesis under the supervision of any computer science professor, regardless of their particular field of expertise.

As a partner of the Max Planck Institute, this university regularly collaborates with world-class tech professionals and innovators. And as a student of the University of Tuebingen, you’ll have the chance to meet and work with those authorities. You can even write your thesis during an apprenticeship with a leading tech company.

3. University of Amsterdam – Master in Artificial Intelligence

The artificial intelligence MSc at the University of Amsterdam is among the most comprehensive programs worldwide. It’s designed to provide students with a broad scope of knowledge about AI and its practical application.

This is a full-time, regular program that lasts for two years and takes place in the university’s Science Park. The tuition fee for Dutch, Swiss, Surinamese, or EU students is €2,314, while other learners will need to pay €16,500. It’s worth mentioning that scholarships are available for all students.

For the first year, the curriculum includes seven core courses meant to establish a strong foundation in machine learning, computer vision, and NLP. The second year consists entirely of electives, both restricted and free-choice. Of course, you’ll wrap up the program with an AI thesis.

This artificial intelligence MSc program offers excellent career prospects. Many alumni have found work in distinguished positions at leading tech or tech-adjacent companies like Google, Eagle Vision, Airbnb, and Volvo.

4. Johns Hopkins University – Artificial Intelligence Master’s Program Online

As one of the leading educational centers in the world, Johns Hopkins University provides exceptional programs and courses in numerous areas. This online AI master’s program is no different. It will give you a solid understanding of the subject in theory and practice.

To earn this degree, you’ll need to pass 10 courses in the total period of five years. Since Johns Hopkins is a U.S. university, the tuition fees are expressed in dollars. The standard fee per course is $6,290. However, this program is a part of the university’s Engineering for Professionals division, and all courses in that division are subject to a special dean’s discount. The actual price you’ll pay, therefore, will be $5,090 per course or $50,900 in total.

The core courses you’ll take will include Introduction to Algorithms or Algorithms for Data Science, Applied Machine Learning, Artificial Intelligence, and Creating AI-Enabled Systems. The rest of the curriculum will consist of six electives – you’ll have 26 to choose from.

The faculty consists of acclaimed experts, and the university has close ties with industry-leading companies. Both of which will help you build your network and connect with professionals who may help advance your career.

5. KTH Sweden – MSc Machine Learning

Housed at the university’s campus in Stockholm, this MSc in machine learning program is a part of the KTHs School of Electrical Engineering and Computer Science. The program examines different facets of machine learning and how they apply to problem-solving in the real world.

The program is broken down into four semesters and lasts for two years total, if completed regularly. Swiss and EU students need not pay fees for program application or tuition. For other learners, the tuition fee for the whole program will be SEK 310,000, while the application fee is SEK 900.

The curriculum consists of mandatory and elective classes, with the electives being conditioned. For example, you’ll need to choose a minimum of six courses from the two groups of Theory and Application Domain.

KTH has an impressive percentage of graduates who found employment – 97%. Of those, half have assumed leadership positions, and one in 10 works in a managerial role. In fact, more than half of KHTs students start working in their respective industries before getting the degree. This serves as proof of the stellar reputation that KHT enjoys nation- and worldwide.

Become an Expert in the Leading Computer Science Disciplines

Getting a masters in AI and ML can help you find your place in these highly competitive industries. Of course, it will be necessary to find a program that suits you to maximize your chances of success.

Whichever program you choose, one thing is certain: Machine learning and artificial intelligence will continue to grow in importance. With a proper education, you’ll be able to keep up the pace and may find yourself among the experts leading the progress in these disciplines.

According to Data USA, degrees in the business field are among the most popular in the United States, with 840,116 degrees in this field alone being awarded in 2020. You went down the commerce route (meaning you have a grasp of business administration, accounting, and applied economics) and now you’re interested in practical applications of your knowledge.

With your commerce degree firmly under your belt, you may feel like a ship without a rudder – aimless and having no idea what direction to go. Happily, the tech field is ready and waiting for you, as a career in computer sciences may await. Here, we ask, “can a commerce student do BSc Computer Science?” The answer may surprise you, especially if you’re worried that a computer science degree’s eligibility requirements are outside the scope of what you learned in your commerce studies.

Background on Commerce and Computer Science

On the surface, commerce and computer science may seem like they go together as well as peanut butter and granite. But if you dig a little deeper into the scope of each subject, you start to realize that there’s more crossover than there first appears:

• Commerce – A degree in commerce gives you a firm grasp of the numbers that lie behind the scenes in a business, with banking, economics, and accounting all falling under your developing areas of expertise. Analytics is also a key part of these courses (especially in the research and data analyst fields), which is where we see some crossover with computer science.
• Computer Science – If commerce is all about the behind-the-scenes numbers in business, computer science handles what goes on under the hood in computing. Software development, data modeling, and analysis all fall under the computer science graduate’s remit, with the ability to pore through data to come to conclusions being essential to this technical subject.

It’s in the analysis that we start to see similarities between commerce and computer science emerge. Yes, commerce focuses more on the numbers behind businesses (and wider economic trends), but the ability to understand the data presented and report on what you see has applications in the computer science field. There’s not a direct crossover, as computer science will require you to learn the “language” in which computers speak, but they are many soft skills you develop in a commerce degree that apply to computer science.

Eligibility for BSc Computer Science

The key questions to ask when considering the issue of whether can commerce student do BSc Computer Science split into two categories:

• The general eligibility requirements to study a BSc in computer science
• Specific requirements that apply to commerce students

Eligibility Criteria for BSc Computer Science

BSc Computer Science degrees don’t require a great deal of computer know-how (though it helps), instead focusing on your grasp of mathematics. Requirements include the following:

• A high school diploma (or your country’s equivalent) that shows solid performance in mathematical subjects.
  • Some degrees require you to achieve a specific Grade Point Average (GPA), though the specific GPA varies depending on where you apply.
• A high level of English proficiency, which can be measured using one (or both) of the following tests:
  • IELTS – Get a minimum score between 6.0 and 7.0
  • TOEFL – Get a minimum score between 90 and 100

Beyond these educational requirements, international students may need to submit copies of their passport and Visa, alongside certified academic transcripts to show they’ve achieved their country’s equivalents of the above grades. Not all courses require this of international students, with some online universities focusing more on your academic skills and less on your country of origin.

In terms of entrance exams, some colleges enforce computer science-specific exams (such as the CUET or CUCET), while others use NPATS or similar, more general exams, to determine proficiency.

Eligibility Criteria for Commerce Students

You may be standing at the starting line of your educational journey, meaning you’ve not yet applied to start your degree in commerce. First, congratulations on thinking so far ahead that you’re wondering “Can a commerce student do BSc Computer Science?” And second, you need to know what high school subjects help you get onto this degree path.

Commerce is a form of business degree, meaning any high school subjects that apply to the economic world help. Subjects like math, finance, economics, and foreign languages are obvious choices. The likes of marketing and computer applications also help (with the latter also laying some groundwork for your later computer science studies.

Much like computer science, you’ll likely have to take an entrance exam when applying to study commerce at most universities. The CSEET, CUET, and SET are common choices, with the first of these exams focusing specifically on those who study commerce to work as company secretaries.

The Possibility of Flexible Eligibility Criteria

Not all colleges require you to take entrance exams, with some even using broader strokes for their eligibility requirements to the point where they provide flexibility for both commerce and computer science students.

Colleges with open curriculums (such as Brown University and Hamilton College) offer more freedom in terms of what you study, with their entry requirements being more flexible as a result. Online institutions, such as the Open Institute of Technology (OPIT) may also offer more flexible entry criteria, sometimes allowing you to transfer credit from one course to another. That type of credit transfer may be ideal for you if you start a degree in commerce only to later decide to go down the computer science route.

Career Prospects for Commerce Students in Computer Science

When it comes to careers for those who hold computer science degrees, the obvious heavy-hitters are software and web development, IT management, and systems architecture. There are also exciting careers in the emerging AI fields that take full advantage of the technical skills you’ll develop as part of a BSc in computer science.

As for the career crossover between commerce and computer science, the key is to think about the skills that a commerce degree gives you that can apply in the computing field. Such skills include the following:

• Analytical Skills – Much like computer science, commerce is all about analyzing the data presented so you can report (and leverage) it for other purposes. Your ability to sit down and pore through the numbers will take you a long way in a computer-related role.
• Problem-Solving Skills – Closely linked to analytical skills, the ability to solve problems requires you to see the data at hand and come up with solutions while accounting for any restrictions presented. In creating commerce models, those restrictions may relate to budget and competencies, while computer science asks you to solve problems while taking system capabilities and limitations into account.
• Communication and Teamwork – Though often considered soft skills (as opposed to the “hard” technical skills you learn in a commerce degree), communication and teamwork are vital. If you need proof, try to work alone in any technical career and you’ll see why it’s so crucial to have these skills.

Potential Career Paths for Commerce Students with a BSc in Computer Science

With so much crossover potential between commerce and computer science, it’s clear that the answer to the question can a commerce student do BSc Computer Science is a resounding “yes.” And once you’ve completed your studies, several career paths await:

• Data Analyst – Reviewing data to find insights (be that into businesses or computer systems) are part of the remit for a data analyst. This role is all about problem-solving, which is a skill you’ll develop in abundance as a commerce and computer science student.
• Business Analyst – Take the ability to gather insights that is required of a data analyst and apply it specifically to areas of improvement in a business to become a business analyst. You’ll combine technical knowledge of a company’s inner workings with complex financial (and computational) models.
• IT Consultant – More computer science-centric than commerce-focused, IT consultants deal with the hows and whys of the computer networks businesses build. Your commerce skills will still come into play though, particularly when explaining how IT benefits businesses financially.
• Financial Technology Specialist – Combining the best of both worlds, this role combines the accounting skills you develop studying commerce with the technical ability needed to understand software and its functions.

Challenges and Considerations for Commerce Students

Though it’s possible for a commerce student to study (and succeed in) computer science, there are some challenges to consider.

The Technical Nature of Computer Science

As you learn the language of numbers in a commerce degree, so must you learn the language of machines when studying computer science. Getting to grips with the lingo (not to mention coding) can present a challenge to more business-minded students.

Balancing Your Workload

There’s an old saying that goes “Don’t burn the candle at both ends,” which is a warning not to pack too much onto your work plate. If you study commerce and computer science simultaneously, there’s a risk you may push yourself too far. Avoiding burnout requires finding the balance between your studies and personal time.

Networking and Practical Experience

As a commerce student, you understand that the world of business is as much about who you know as what you know. Finding the right people to take a chance on you, thus giving you practical experience, can be tough. But when armed with a pair of degrees in subjects that complement one another, you’re in a better position to build connections with people who can help you go far.

From Commerce to Computing – Is It Right for You?

So, can a commerce student do BSc Computer Science?

The answer isn’t just “yes,” but that it’s actually a great direction to go. Where a commerce degree equips you with a nice mix of technical knowledge and soft skills, a computer science course gives you even more practical knowledge that allows you to enter more specialized fields. However, your interest in each subject plays a role, as your ability (and passion) for studying hinges on your desire to dig into the more technical world of computing.

Assuming you have a genuine interest (and meet the appropriate eligibility criteria), supplementing your commerce studies with computer science can open up many career paths.

AI and machine learning are like an unstoppable tidal wave in today’s world. We’ve already seen the crest of that wave appear over the horizon with increased automation in businesses and the emergence of apps like ChatGPT. But in the coming years, the wave will engulf the world, making AI big business.

That’s supported by statistics from Statista, too, with reports that the AI market that was worth $200 billion (approx. €185 billion) in 2022 will be worth a staggering $2 trillion (approx. €1.85 trillion) in 2030. The point is that massive growth is coming in AI, and the right Master’s in AI is the key for you to be a part of that growth rather than getting stuck in an industry that gets consumed by it.

Top European Programs for Masters in AI and ML

In choosing the MSc artificial intelligence programs that appear on this list, we looked at factors ranging from the quality (and variety) of course content to who provides the degree. The three courses highlighted here are among Europe’s best to offer to European and overseas students.

Master in Artificial Intelligence (Universita di Bologna)

Though it’s held in Italy, this Master’s program is delivered in English as part of Universita di Bologna’s computer science program. It’s an on-campus course, meaning you’ll have to move to Bologna to attend.

The course provides a solid grounding in the foundations of AI over two years. You’ll get to grips with topics like machine learning and natural language processing, in addition to touching on the ethical and social issues that the rise of AI brings to the table.

The course is welcoming to international students, as it currently has a 77% ratio of international students who don’t come from Bologna. To apply, you must complete an application on the Studenti Online program, along with a mandatory form. Failure to follow this procedure leads to your application being discarded. Applicants don’t necessarily need to hold a Bachelor’s degree, though they must demonstrate a transcript of record that shows they have earned at least 150 ECTS or CFU credits in majors like computer science, mathematics, statistics, and physics.

The course page boasts that 90.5% of its 2021 graduates were happy with their degrees. It’s natural to assume most of these graduates leveraged their Master’s in artificial intelligence to move into careers in the field.

Master in Applied Data Science & AI (OPIT)

If you want to master artificial intelligence with a sprinkling of applying that mastery to the data science industry, OPIT’s course is right for you. It’s an 18-month course (though a 12-month fast-track version is available) that is fully online and delivers 90 ECTS credits. The first term covers the foundational aspects of AI, including subjects like machine learning and data science. But the second term stands out as it moves study from the theoretical to the practical by challenging you to solve real-world problems with your knowledge.

As an online program, it’s available to anybody anywhere, with entry requirements also being flexible. You’ll need a BSc degree, even one from a non-technical field, and should demonstrate English proficiency up to the B2 level with appropriate certification. Don’t worry if you don’t have an English language certification because OPIT offers its own that you can take before registering for the course.

Career-wise, the course is a good option because it occupies an interesting middle-ground between theory and practicality. The second term, in particular, equips you with skills that you can apply directly in fields as varied as IT business analysis, business intelligence, and data science.

MSc in Advanced Computer Science (University of Oxford)

Though it’s not marketed directly as a Master’s in machine learning and artificial intelligence, the University of Oxford’s program gives you excellent qualifications in both. It’s also delivered by an institution that EduRank names as the best for AI in the UK, and sixth-best in the world. The course examines advanced machine learning and computer security techniques, focusing on computational models and the algorithms behind them.

It’s a full-time program demanding 35 hours of weekly study, 15 of which you’ll spend on campus with the other 20 dedicated to self-study. It’s also a tough nut to crack for applicants, as the University of Oxford has a low 18% acceptance rate. You’ll need a first-class undergraduate degree with honors (or an equivalent) in mathematics or computer science to stand a chance of getting into one of the UK’s most prestigious universities.

Those tough entry requirements pay off later on, though, as the words “University of Oxford” on a CV immediately make employers stand up and pay attention. The wide-ranging approach of the program also means you’re not focusing solely on AI, opening up career opportunities in other fields related to math and statistical analysis.

Data Science Master – Europe’s Best Options

Data science is an industry that requires you to translate your understanding of algorithmic theory to transform complex data sets into actionable insights. It’s also an industry that’s making increasingly heavy use of AI tools, making a Master’s in data science a great companion (or alternative) to the best artificial intelligence Master in Europe. As you noticed above, OPIT’s MSc AI program includes elements of data science, though the two programs here (covered in brief) are excellent choices as standalone programs.

MSc Data Sciences and Business Analytics (Essec Business School)

This hybrid course lasts for either one or two years, depending on your background, and focuses on the application of data sciences in a business context. It’s also ranked as the fourth-best Master’s in business analytics in the world by QS World University Rankings.

That high ranking is backed up by the university’s own statistics, which state that over half of its students get jobs before they even complete the course. Essec has a 100% career success rate for graduates in less than six months from completion of the Master’s, making this a great choice for career-focused students. Google, Amazon, JP Morgan Chase, and PwC count as some of the top recruiters that keep their eye on graduates from this program.

Admission requires a degree in a related technical subject, such as engineering, science, or business, from a leading university. That degree also impacts the version of the program you take, as a three-year BSc means you take the two-year Master’s, while those who have a four-year BSc under their belts take the one-year version, assuming they meet other requirements.

Data Science, Technology, and Innovation (University of Edinburgh)

With over 13,000 international students, the University of Edinburgh welcomes overseas students who want to expand their knowledge. Its MSc data science program is no different, buoyed by the fact that it’s an online course that doesn’t require you to move to the less-than-sunny climate of Edinburgh.

It’s a part-time program that relies on self-study, though it provides you with plenty of interactive resources to help along the way. The program is something of an umbrella course as it focuses on equipping students with the knowledge they need to enter the data science field across industries as diverse as medicine, science, and even the arts.

You’ll need the equivalent of an Upper Second-Class Honors degree that has elements of programming before applying. Ideally, you’ll also have evidence of mathematical skill, either through taking math classes in your undergraduate studies or by demonstrating the equivalent of an English A-Level in math through other qualifications.

Factors to Consider When Choosing an Artificial Intelligence Master’s

The five programs highlighted here all help you master artificial intelligence, with many also providing a practical grounding that puts you in good stead for your future career. But if you want to do more research (and that’s always a good idea), the following factors should be on your mind when checking other programs:

• Course Curriculum – The content of your course impacts what you can do once you have your MSc under your belt. Focus on programs that teach tangible skills applicable to the field you wish to enter.
• Faculty – Always check the credentials of the program’s creators and administrators, particularly in terms of industry experience, to confirm they have the relevant tools.
• Tuition and Financial Aid – Master’s programs aren’t cheap (you’ll pay several thousand euros for even an online course), so check you can budget accordingly for the program. Many universities offer financial aid options, from scholarships to student loans, that can help in this area.
• Location – The location isn’t really an issue if you take an online course, but it impacts your decision if you decide to study on-campus. Remember that you’ll spend at least a year of your life on the course (often two years) so you need to gel well with the place in which you’ll live.
• Networking and Industry – Does the course provider have connections to major industry players? Does it offer career advice, ideally via a specialized office or program? These are the types of questions to ask when assessing a university’s capacity for networking and career advancement.

Become a Master in Artificial Intelligence

A Master’s degree in artificial intelligence is your entry point into a growing industry that’s already on the verge of taking the world by storm. That is, assuming you choose the right program. The five highlighted here all land in the “right program” category by virtue of the tuition you receive, the reputation of the institution, and their accessibility to European and overseas students.

Research each program (and any others you consider) extensively before making a choice. Remember that it’s not always about the course or its reputation – it’s about how the course helps you achieve the specific learning goals you need to achieve to get ahead in your chosen career.

Do you tend to get all technical about how computers work? Or, do you prefer to put your thinking cap on and dig deep into theory and research?

These questions matter because they can help you choose between BCA and BSc Computer Science. One focuses on practical knowledge, while the other explores the nitty-gritty behind technical concepts.

In this BCA vs. BSc computer science: which is better guide, we’ll provide detailed information about the two courses and help point you in the right direction.

BCA: Bachelor of Computer Applications

To resolve the BSc computer science vs. BCA confusion, we need to discuss both in detail. Let’s start with BCA: Bachelor of Computer Applications.

Overview of the BCA Program

Duration

BCA is typically a three-year professional undergraduate course focused on learning computer languages and applications. Since the focus is on applications, the BCA program is a software-oriented course (which is great for those who don’t enjoy learning too much theory).

Course Structure

The course structure depends on your chosen university. In most cases, you’ll have five core subjects per semester. Additionally, you’ll choose electives to learn more about specific computer-related topics.

Eligibility Criteria

Every university is free to set its own criteria for enrolling in a BCA program. Still, there are some tendencies you should know about. Students who studied arts, commerce, or science are most welcome to apply. Some universities may also have specific entrance exams that test subject-related knowledge.

Key Subjects Covered in BCA

As mentioned, the course structure in BCA programs varies (depending on the university). Regardless, every student needs to cover core subjects that will equip them to conquer the industry.

Programming Languages

Programming languages are like human languages. But rather than allowing communication among people, these languages let us “talk to” computers. This subject covers the basics of Java, HTML, C, C++, and others.

Database Management

Think of database management systems as computerized data-keeping solutions. Learning how to work with these systems is essential to ensure proper information storage and retrieval, and this is exactly what students learn on this course.

Web Development

Want to know how to create and maintain websites? This subject offers insight into behind-the-scenes work that goes into developing online stores, social networks, blogs, business websites, and others.

Networking

This subject explores the secret language in which computers, systems, and devices communicate with one another. All of which sheds light on how to connect them to share data.

Career Prospects After BCA

A degree in computer application opens doors to various career paths. Here are the job positions you can apply for after completing your studies:

• Game Designer
• System Specialist
• Technical Support
• Web Designer
• Network Administrator
• System Manager
• Software Tester
• Programmer

In terms of continuing your education, these options are available:

• Master in Computer Application
• Master of Science in Information Technology
• Master in Business Administration

BSc Computer Science: Bachelor of Science in Computer Science

If you want to know which is better: BCA or BSc Computer Science, you need to learn more about them. Since we’ve covered the BCA program, it’s time to discuss BSc Computer Science.

Overview of the BSc Computer Science Program

Duration

Students can choose between two options: regular and fast-track. The former lasts three years, while the latter lasts two.

Course Structure

One of the first things students are interested in is the course structure. In most cases, you’ll have six terms – five terms of courses and one for the final project (dissertation).

That being said, remember that every university sets its own course structure.

Eligibility Criteria

Universities set their eligibility criteria. Therefore, each institution has unique standards students have to meet to enroll. Some universities have strict requirements, the most common being a background in physics, chemistry, or mathematics.

If you don’t meet these criteria, no worries. Online degree programs like the Open Institute of Technology (Opit) have easy-to-meet entry requirements, such as English proficiency (at least a B2 level) and high school education.

Key Subjects Covered in BSc Computer Science

The BSc Computer Science program features several core subjects.

Programming Languages

During this course, students learn how to “speak” programming languages. They’re introduced to fundamental concepts and common logical and/or syntactical problems they need to resolve.

Data Structures and Algorithms

If you want to learn how to organize data or solve a particular problem, you’ll find the answers to these questions and more in this course.

Operating Systems

Every OS is an entity of its own with unique anatomies, functions, and layers.

Computer Networks

A computer network is a cluster of interconnected dots that communicate with each other and transfer data. During this course, you’ll learn how this communication works.

Career Prospects After BSc Computer Science

What can you do after BSc Computer Science? The program allows you to explore a wide array of job positions:

• Software Developer/Engineer
• Web Developer
• Data Scientist
• Cyber Security Analyst
• Database Architect
• IT Business Analyst
• App/Game Developer
• Database Architect

BSc Computer Science offers an excellent theoretical foundation. It’s no surprise, therefore, that many students decide to pursue higher education. Here are some of the available options:

• Master of Science in Computer Science
• Master in Computer Management
• Bachelor of Technology in Computer Science

Key Differences Between BCA and BCs Computer Science

Want to know which is better: BSc Computer Science or BCA? To get the answer, you need to learn about the differences between the two degrees.

Course Focus

You wouldn’t be wrong if you said the two programs are similar. But there’s a significant difference between BCA and BSc Computer Science: course focus. BCA is all about application it centers on current technology, computing, and programming trends. The program is ideal for students who are more interested in practical knowledge.

On the other hand, BSc Computer Science is perfect for those who like reading theory, doing research, and learning about different computer-related concepts.

Curriculum

The battle between theoretical and practical knowledge is (of course) reflected in the curriculum. The subjects BCA features develop practical, application-oriented skills, while BSc Computer Science prefers theory.

Eligibility Criteria

While trying not to sound like a broken record, let’s repeat it once again: it depends on the university. As a rule of thumb, BSc Computer Science has stricter criteria.

Career Opportunities

As far as career opportunities are concerned, both programs will set you up for success in the industry. Of course, each program opens doors to different fields. Students who complete the BCA program pursue jobs in IT or software development. Those who complete the BSc Computer Science program usually continue their education or work as researchers.

Which Is Better: BCA or BSc Computer Science?

Given that each program focuses on different aspects, it’s hard to say one stands out as “the best.” Every person is unique, and what suits you may not work for someone else. It all comes down to your future plans and ambitions. Going down the technical-heavy route is great for coding or anything else that calls for theoretical applications, but it won’t help much if you need experience in something practical, like game design. By the same token, you’ll need to draw from a well of technical knowledge when you’re working in data science or IT analysis. The choice comes down to balancing these three factors:

• Personal interest and aptitude – Do you prefer theory or practice?
• Career goals – What do you want to do after completing the program?
• Future education plans – Do you want to continue your education after the program?

Answer these questions to get a better idea of whether you should opt for BCA or BSc Computer Science. Remember, there’s no wrong answer. Picking a course isn’t like playing Russian roulette. It’s more like playing those little arcade machines that guarantee a prize with every turn – there’s no way to lose! Whatever you choose, you can build a fruitful career with computers. The path you decide to take solely depends on whether you prefer theory or practice.

Pros and Cons of Each Course

What are the strengths and weaknesses of each course? Find out here.

BCA

Pros:

• Offers practical knowledge
• Follow the latest industry trends
• Less strict entry requirements
• Job-oriented

Cons:

• Challenging course structure
• Technology rapidly evolves, so you need to constantly update your skills to stay current

BCs in Computer Science

Pros:

• Offers excellent theoretical knowledge
• Great for those who want to continue their education
• Ideal for researchers
• Provides a strong foundation

Cons:

• Stricter eligibility criteria
• Some consider it too theoretical

Tips for Making the Right Choice

These valuable tips can help you choose the right program:

• Consider your expectations. Think about what you want to get from this course and where you want it to take you career-wise.
• Study the curriculum. The curriculum is like a program’s CV. If you want to know whether it’s a good fit for you, you need to research it carefully.
• Talk to someone who completed the program you’re interested in. A person who completed the course can offer valuable intel and help you determine whether you’re on the right track.
• Consult an academic advisor. An advisor can analyze your preferences and put them into a concrete suggestion on which direction you should take.
• Think about what you want to do next. Do you want to continue your education or find a job in the industry? The answer can help you make the right decision.

Find Your Passion

The biggest difference between BSc Computer Science and BCA lies in the curriculum. With the former, the subjects focus on obtaining theoretical knowledge to set the ground for further education or research. On the other hand, BCA focuses on practical skills and exploring current trends.

Instead of wondering which is best: BCA or BSc Computer Science, think about your preferences and requirements. Explore your priorities, research both options, talk to professionals, and you’ll recognize the better fit.