You may have heard the catchy phrase “data is the new oil” floating around. The implication is that data in the 21st century is what oil was in the 20th – the biggest industry around. And it’s true, as the sheer amount of data each person generates when they use the web, try out an app, or even buy from a store is digital “oil” for the companies collecting that data.

It’s also the fuel that powers the current (and growing) wave of artificial intelligence (AI) tools emerging in the market. From ChatGPT to the wave of text-to-speech tech flooding the market, everything hinges on information, and people who can harness that data through algorithms and machine learning practices are in high demand.

That’s where you can come in. By taking a Master’s degree in artificial intelligence online, you position yourself as one of the people who can help the new “digital oil” barons capitalize on their finds.

Factors to Consider When Choosing an Online AI Master’s Program

When choosing an artificial intelligence online Master’s, you have to consider more than the simple accessibility the course offers. These factors help you to weed out the also-ran programs from the ones that help you to advance your career:

• Accreditation – Checks for accreditation come in two flavors. First, you need to check the program provider’s credentials to ensure the degree you get from your studies is worth the paper on which it’s printed. Second, you have to confirm the accreditation you receive is something that employers actually want to see.
• Curriculum – What does your artificial intelligence online Master degree actually teach you? Answer that question and you can determine if the program serves the career goals you’ve set for yourself.
• Faculty Expertise – On the ground level, you want tutors with plenty of teaching experience and their own degrees in AI-related subjects. But dig beyond that to also discover if they have direct experience working with AI in industry.
• Program Format – A self-study artificial intelligence Master’s program’s online nature means they offer some degree of flexibility. But the course format plays a role in your decision, given that some rely solely on self-learning whereas others include examinations and live remote lectures.
• Tuition and Financial Aid – A Master’s degree costs quite a bit depending on area (prices range from €1,000 to €20,000 per year), so you need to be in the appropriate financial position. Many universities offer financial aid, such as scholarships, grants, and payment programs, that may help here.
• Career Support – You’re likely not studying for Master of artificial intelligence online for the joy of having a piece of paper on your wall. You want to build a career. Look for institutions that have strong alumni networks, connections within industry, and dedicated careers offices or services.

Top Online AI Master’s Programs Ranked

In choosing the best Master’s in artificial intelligence online programs, we looked at the above factors in addition to the key features of each program. That examination results in three online courses, each offering something a little different, that give you a solid grounding in AI.

Master in Applied Data Science & AI (OPIT)

Flexibility is the name of the game with OPIT’s program, as it’s fully remote and you get a choice between an 18-month course and a fast-tracked 12-month variant. The latter contains the same content as the former, with the student simply dedicating themselves to more intensive course requirements.

The program comes from an online institution that is accredited under both the Malta Qualification Framework and European Qualification Framework. As for the course itself, it’s the focus on real-life challenges in data science and AI that makes it so attractive. You don’t just learn theory. You discover how to apply that theory to the practical problems you’ll face when you enter the workforce.

OPIT has an admissions team who’ll guide you through getting onto the course, though you’ll need a BSc degree (in any field) and the equivalent of B2-level English proficiency to apply. If English isn’t your strong suit, OPIT also offers an in-house certification that you can take to get on the course. Financial aid is available through scholarships and funding, which you may need given that the program can cost up to €6,500, though discounts are available for those who apply early.

Master in Big Data, Artificial Intelligence, and Disruptive Technologies (Digital Age University)

If data is the new oil, Digital Age University’s program teaches you how to harness that oil and pump it in a way that makes you an attractive proposition for any employer. Key areas of study include the concept and utilization of Big Data (data analytics plays a huge role here), as well as the Python programming skills needed to create AI tools. You’ll learn more about machine learning models and get to grips with how AI is the big disruptor in modern business.

Tuition costs are reasonable, too, with this one-year course only costing €2,600. Digital Age University runs a tuition installment plan that lets you spread your costs out without worrying about being charged interest. Plus, your previous credentials may put you in line for a grant or scholarship that covers at least part of the cost. All first-year students are eligible for the 10% merit-based scholarship again, dependent on prior education). There’s also a 20% Global Scholarship available to students from Asia, Africa, the Middle East, and Latin American countries.

Speaking of credentials, you can showcase yours via the online application process or by scheduling a one-on-one call with one of the institution’s professors. The latter option is great if you’re conducting research and want to get a taste of what the faculty has to offer.

Master in Artificial Intelligence (Three Points Digital Business School)

Three Points Digital Business School sets its stall out early by pointing out that 83% of companies say they’ll create new jobs due to AI in the coming years. That’s its way of telling you that its business-focused AI course is the right choice for getting one of those jobs. After teaching the fundamentals of AI, the course moves into showing you how to create AI and machine learning models and, crucially, how to apply those models in practical settings. By the end, you’ll know how to program chatbots, virtual assistants, and similar AI-driven tools.

It’s the most expensive program on this list, clocking in at €7,500 for a one-year course that delivers 60 ECTS credits. However, it’s a course targeted at mature students (half of the current students are 40 years old), and it’s very much career-minded. That’s exemplified by Three Points’ annual ThinkDigital Summit, which puts some of the leading minds in AI and digital innovation in front of students.

Admission is tougher than for many other Master’s in artificial intelligence online programs as you go through an interview process in addition to submitting qualifications. Every candidate is manually assessed via committee, with your experience and business know-how playing as much of a role as any technical qualifications you have.

Tips for Success in an Online AI Master’s Program

Let’s assume you’ve successfully applied to an artificial intelligence online Master’s program. That’s the first step in a long, often complex, journey. Here are some tips to keep in mind and set up for the future:

• Manage your time properly by scheduling your study, especially given that online courses rely on students having the discipline needed for self-learning.
• Build relationships with faculty and peers who may be able to connect you to job opportunities or have ideas for starting their own businesses.
• Stay up-to-date on what’s happening with AI because this high-paced industry can leave people who assume what they know is enough behind.
• Pursue real-world experience wherever you can, both through the practical assessments a program offers and internship programs that you can add to your CV.

Career Opportunities With a Master’s in Artificial Intelligence

You need to know what sorts of roles are available on the digital “oil rigs” of today and the future. Those who have an artificial intelligence online Master degree take roles as varied as data analyst, software engineer, data scientist, and research scientist.

Better yet, those roles are spread across almost all industries. Grand View Research tells us that we can expect the AI market to enjoy a 37.3% compound annual growth rate between 2023 and 2030, with that growth making AI-based roles available on a near-constant basis. Salary expectations are likely to increase along with that growth, with the current average of around €91,000 for an artificial intelligence engineer (figures based on Germany’s job market) likely to be a baseline for future growth.

Find the Right Artificial Intelligence Master’s Programs Online

We’ve highlighted three online Master’s programs with a focus on AI in this article, each offering something different. OPIT’s course leans heavily into data science, giving you a specialization to go along with the foundational knowledge you’ll gain. Digital Age University’s program places more of a focus on Big Data, with Three Points Digital Business School living up to its name by taking a more business-oriented approach.

Whatever program you choose (and it could be one other than the three listed here), you must research the course based on the factors like credentials, course content, and quality of the faculty. Put plenty of time into this research process and you’re sure to find a program that aligns with your goals.

Machines that can learn on their own have been a sci-fi dream for decades. Lately, that dream seems to be coming true thanks to advances in AI, machine learning, deep learning, and other cutting-edge technologies.

Have you used Google’s search engine recently or admired the capabilities of ChatGPT? That means you’ve seen machine learning in action. Besides those renowned apps, the technology is widespread across many industries, so much so that machine learning experts are in increasingly high demand worldwide.

Chances are there’s never been a better time to get involved in the IT industry than today. This is especially true if you enter the market as a machine learning specialist. Fortunately, getting proficient in this field no longer requires enlisting in a college – now you can finish a Master in machine learning online.

Let’s look at the best online Masters in machine learning and data science that you can start from the comfort of your home.

Top MSc Programs in Machine Learning Online

Finding the best MSc machine learning online programs required us to apply certain strict criteria in the search process. The following is a list of programs that passed our research with flying colors. But first, here’s what we looked for in machine learning MSc courses.

Our Criteria

The criteria we applied include:

• The quality and reputation of the institution providing the course
• International degree recognition
• Program structure and curriculum
• Duration
• Pricing

Luckily, numerous world-class universities and organizations have a machine learning MSc online. Their degrees are accepted around the world, and their curricula count among the finest in the market. Take a look at our selection.

Imperial College London – Machine Learning and Data Science

The Machine Learning and Data Science postgraduate program from the Imperial College in London provides comprehensive courses on models applicable to real-life scenarios. The program features hands-on projects and lessons in deep learning, data processing, analytics, and machine learning ethics.

The complete program is online-based and relies mostly on independent study. The curriculum consists of 13 modules. With a part-time commitment, this program will last for two years. The fee is the same for domestic and overseas students: £16,200

European School of Data Science & Technology – MSc Artificial Intelligence and Machine Learning

If you need a Master’s program that combines the best of AI and machine learning, the European School of Data Science & Technology has an excellent offer. The MSc Artificial Intelligence and Machine Learning program provides a sound foundation of the essential concepts in both disciplines.

During the courses, you’ll examine the details of reinforcement learning, search algorithms, optimization, clustering, and more. You’ll also get the opportunity to work with machine learning in the R language environment.

The program lasts for 18 months and is entirely online. Applicants must cover a registration fee of €1500 plus monthly fees of €490.

European University Cyprus – Artificial Intelligence Master

The European University in Cyprus is an award-winning institution that excels in student services and engagement, as well as online learning. The Artificial Intelligence Master program from this university treats artificial intelligence in a broader sense. However, machine learning is a considerable part of the curriculum, being taught alongside NLP, robotics, and big data.

The official site of the European University Cyprus states the price for all computer science Master’s degrees at €8,460. However, it’s worth noting that there’s a program for financial support and scholarships. The duration of the program is 18 months, after which you’ll get an MSc in artificial intelligence.

Udacity – Computer Vision Nanodegree

Udacity has profiled itself as a leading learning platform. Its Nanodegree programs provide detailed knowledge on numerous subjects, such as this Computer Vision Nanodegree. The course isn’t a genuine MSc program, but it offers specialization for a specific field of machine learning that may serve for career advancement.

This program includes lessons on the essentials of image processing and computer vision, deep learning, object tracking, and advanced computer vision applications. As with other Udacity courses, learners will enjoy support in real-time as well as career-specific services for professional development after finishing the course.

This Nanodegree has a flexible schedule, allowing you to set a personalized learning pace. The course lasts for three months and has a fee of €944. Scholarship options are also available for this program, and there are no limitations in terms of applying for the course or starting the program.

Lebanese American University – MS in Applied Artificial Intelligence

Lebanese American University curates the MS in Applied Artificial Intelligence study program, led by experienced faculty members. The course is completely online and focuses on practical applications of AI programming, machine learning, data learning, and data science. During the program, learners will have the opportunity to try out AI solutions for real-life issues.

This MS program has a duration of two years. During that time, you can take eight core courses and 10 elective courses, including subjects like Healthcare Analytics, Big Data Analytics, and AI for Biomedical Informatics.

The price of this program is €6,961 per year. It’s worth noting that there’s a set application deadline and starting date for the course. The first upcoming application date is in July, with the program starting in September.

Data Science Degrees: A Complementary Path

Machine learning can be viewed as a subcategory of data science. While the former focuses on methods of supervised and unsupervised AI learning, the latter is a broad field of research. Data science deals with everything from programming languages to AI development and robotics.

Naturally, there’s a considerable correlation between machine learning and data science. In fact, getting familiar with the principles of data science can be quite helpful when studying machine learning. That’s why we compiled a list of degree programs for data science that will complement your machine learning education perfectly.

Top Online Data Science Degree Programs

Purdue Global – Online Bachelor of Science Degree in Analytics

Data analytics represents one of the essential facets of data science. The Online Bachelor of Science Degree in Analytics program is an excellent choice to get familiar with data science skills. To that end, the program may complement your machine learning knowledge or serve as a starting point for a more focused pursuit of data science.

The curriculum includes nine different paths of professional specialization. Some of those concentrations include cloud computing, network administration, game development, and software development in various programming languages.

Studying full-time, you should be able to complete the program within four years. Each course has a limited term of 10 weeks. The program in total requires 180 credits, and the price of one credit is $371 or its equivalent in euros.

Berlin School of Business and Innovation – MSc Data Analytics

MSc Data Analytics is a postgraduate program from the Berlin School of Business and Innovation (BSBI). As an MSc curriculum, the program is relatively complex and demanding, but will be more than worthwhile for anyone wanting to gain a firm grasp of data analytics.

This is a traditional on-campus course that also has an online variant. The program focuses on data analysis and extraction and predictive modeling. While it could serve as a complementary degree to machine learning, it’s worth noting that this course may be the most useful for those pursuing a multidisciplinary approach.

This MSc course lasts for 18 months. Pricing differs between EU and non-EU students, with the former paying €8,000 and the latter €12,600.

Imperial College London – Machine Learning and Data Science

It’s apparent from the very name that this Imperial College London program represents an ideal mix. Machine Learning and Data Science combines the two disciplines, providing a thorough insight into their fundamentals and applications.

The two-year program is tailored for part-time learners. It consists of core modules like Programming for Data Science, Ethics in Data Science and Artificial Intelligence, Deep Learning, and Applicable Mathematics.

This British-based program costs £16,200 yearly, both for domestic and overseas students. Some of the methods include lectures, tutorials, exercises, and reading materials.

Thriving Career Opportunities With a Masters in Machine Learning Online

Jobs in machine learning require proper education. The chances of becoming a professional in the field without mastering the subject are small – the industry needs experts.

A Master’s degree in machine learning can open exciting and lucrative career paths. Some of the best careers in the field include:

• Data scientist
• Machine learning engineer
• Business intelligence developer
• NLP scientist
• Software engineer
• Machine learning designer
• Computational linguist
• Software developer

These professions pay quite well across the EU market. The median annual salary for a machine learning specialist is about €70,000 in Germany, €68,000 in the Netherlands, €46,000 in France, and €36,000 in Italy.

On the higher end, salaries in these countries can reach €98,000, €113,000, €72,000, and €65,000, respectively. To reach these more exclusive salaries, you’ll need to have a quality education in the field and a level of experience.

Become Proficient in Machine Learning Skills

Getting a Master’s degree in machine learning online is convenient, easily accessible, and represents a significant career milestone. With the pace at which the industry is growing today, it would be a wise choice.

Since the best programs offer a thorough education, great references, and a chance for networking, there’s no reason not to check out the courses on offer. Ideally, getting the degree could mark the start of a successful career in machine learning.

Take a sprinkling of math, add some statistical analysis, and coat with the advanced programming and analytics that enables people to pore through enormous batches of data and you have the recipe for a data scientist.

These professionals (and their data-based talents) are sought after in industries of all shapes and sizes. Every sector from healthcare, finance, and retail to communications and even the government can make use of the skills of data scientists to advance. That’s great news if you’re considering completing your Master’s degree in the subject, as your degree is the key that can unlock the door to a comfortable five-figure salary.

Here, we look at the Master’s in data science salary and explain what you can do to maximize your potential.

Masters in Data Science: An Overview

As a postgraduate degree course, a Masters in data science builds on some of the core skills you’ll learn in a computer science or information technology degree. Think of it as a specialization. You’ll expand on the programming and analytical skills you’ve already developed to learn how to extract actionable insights from massive datasets. In the world of Big Data (where companies generate more data than at any other point in history), those skills are more important than ever.

Speaking of skills, you’ll develop or hone the following when studying for your Master’s in data science:

• Data Analysis – The ability to analyze data (i.e., interpret what seemingly random datasets tell you) is one of the first skills you’ll pick up in your degree.
• Data Visualization – Where your analysis helps you to see what you’re looking at, data visualization is all about representing that data visually so that others see what you see.
• AI and Machine Learning – The nascent technologies involved in the artificial intelligence sector revolve around data, in addition to many modern AI technologies being helpful for analyzing data. You’ll learn both sides, developing the skills to both create and use AI.
• Software Engineering and Programming – Don’t assume the programming skills you have from your previous degree will go to waste, as you’ll need them for a data science Master’s. You’ll use plenty of new tools, in addition to picking up more skills in languages like Python, SQL, and R.
• Soft Skills – A Master’s in data science isn’t all technical. You’ll develop some soft skills that prove useful in the workplace, such as communication, basic teamwork, and management. Most data science courses also teach ethics so you can get to grips with the idea of doing the right thing with data.

The Top Universities for a Data Science Masters

According to the university rating website Collegedunia, there are more than 60 leading data sciences universities in the United States alone, each offering both Bachelor’s and Master’s degrees in the subject. It ranks the following as the top five institutions for getting your Master’s in data science:

• MIT – As the top data science university in the world (according to the QS Global Rankings), MIT is the first choice for any prospective student.
• Harvard University – The “Harvard” name carries weight regardless of the course you choose. Data scientists have their pick of a standard Master’s in data science or a course dedicated to health data science.
• Columbia University – Those who want to fast-track their studies may find that the intensive one-year data science Master’s that Columbia offers is a better choice than traditional two-year courses.
• John Hopkins University – Though it’s best known as one of America’s best medical schools, John Hopkins also has a strong data science department. It may be a great choice for those who want to use their data science skills to get into the medical field.
• Northwestern University – Ranking at 30 in the QS Global Rankings, Northwestern offers Master’s degrees in both data science and analytics, with the latter expanding on one of the core skills needed for data science.

Masters in Data Science Salary Potential

As great as the skills you’ll get will be, you want to know more about the Master’s in data science salary you can expect to earn.

The good news is that a strong salary isn’t just possible. It’s likely. According to Indeed, the average salary for a data scientist is £49,749 in the UK. Cult.Honeypot has interesting figures for Europe as a whole, noting that the average data scientist on the continent earns €60,815, which matches up well to general salary expectations of €60,000. You can also expect a position in this field to come with numerous benefits, including medical insurance (where relevant) and flexible working conditions.

Of course, there are several factors that influence your specific earning power:

• Geographic location
• The specific industry in which you work
• Your experience level
• The size of the company for which you work

For example, a brand-new graduate who takes a position at a start-up in a non-tech industry may find that they earn at the lower end of the scale, though they’ll develop experience that could serve them well later on.

Data scientists also tend to have higher salary prospects than those in comparable fields. For example, more data from Indeed shows us that data scientists in the UK earn more, on average, than software engineers (£49,409), computer scientists (£45,245), and computer engineers (£24,780). Furthermore, a Master’s in data science is wide-ranging enough that it’ll give you many of the skills you need for the above industries, assuming you’d want a career change or discover that data science isn’t for you.

Benefits of a Masters in Data Science for Earning Power

It’s clear that the Master’s in data science salary potential is strong, with mid-five-figure salaries being the standard (rather than the exception) for the industry. But there are benefits beyond potential earnings that make the Master’s course a good one to take.

More Job Opportunities

Data science is everywhere in modern industry because every company produces data. You can apply your skills in industries like healthcare, manufacturing, and retail, meaning you have plenty of job opportunities. The research backs this statement up, too, with figures from Polaris Market Research suggesting a 27.6% compound annual growth rate (CAGR) for the data science industry between 2022 and 2030.

Greater Job Security

The encroachment of AI into almost every aspect of our lives has many people worried about job security. Some even speculate that machines will take over many roles in the coming years. Data scientists don’t have to worry about that. Not only will you use AI to advance your research, but you may also be responsible for further developments in the AI and machine learning fields. All of which will make you crucial to the continuation of the AI trend.

Opportunities for Career Advancement

The salary figure quoted above (average salary of €60,815) is for a fairly standard data science role. Opportunities for career advancement exist, whether that be simply moving into a more senior position in a company or taking control of a team, thus adding management to your skill set. Those who prefer conducting research will also find that many universities and large companies have teams dedicated to using data science to create social and commercial change.

Tips for Maximizing Earnings With a Masters in Data Science

With the Master’s in data science salary potential already being attractive enough (six figures is a great start), you may not worry too much about maximizing your earning potential at the start of your career. But as you get deeper into your working life, the following tips will help you get more money in return for the skills you bring to the table.

1 – Choose the Right University and Program

Universities aren’t built equally, with some carrying more weight than others. For example, a data science Master’s degree from MIT holds huge weight because it’s one of America’s top universities for the subject. Employers know what the school is about, understand that those who study there undergo superb training, and will thus be more willing to both hire and offer more money to its graduates. The point is that where you go (and what you study in your course) influences how employers see you, which also influences your earning potential.

2 – Gain Relevant Work Experience

As with any career path, what you learn along the path is as valuable as the skills you pick up when studying. You can get a head start on other data science graduates if you take on internships or get involved in research projects while studying, giving you some work experience to add to your resume that could lead to higher initial salary offers.

3 – Leverage Networking and Connections

Meeting the right people at the right times can do wonders for your career. Studying for a Master’s in data science exposes you to professors (and even people who work in the industry) who can put you in touch with people who offer roles in the industry. Continuous building on these connections, from staying active in the industry to leveraging social media, offers more opportunities for advancement.

4 – Stay Up-to-Date With Industry Trends

Data science is a fast-moving sector, with constant advancements occurring at both the high level (the evolution of AI) and in terms of how we use data science in different industries. Keeping on top of these advancements means you stay “in the know” and can see potential career paths branching out before you.

5 – Pursue Additional Qualifications

Keeping with the theme of staying up-to-date, how you build on your skills via continuing education can influence your salary potential. A Master’s degree in data science is impressive. But a degree supplemented by specialized certifications, proof of bootcamp completion, and any other accolades puts you ahead of the pack of other graduates.

Turn Your Master’s in Data Science Into a Great Career

In addition to opening you up to an exciting career in a field that’s undergoing tremendous growth, a Master’s in data science comes with mid-five-figure salary potential. You can boost your Master’s in data science salary expectations through networking, specialization, and simply staying up-to-date with what’s happening in the industry.

Granted, there are time and monetary commitments involved. You usually dedicate two years of your life to getting your degree (though some universities offer one-year data science Master’s courses) and you’ll pay a five-figure sum for your education. But the benefits on the backend of that commitment are so vast that a Master’s in data science may be the key to unlocking huge earnings in the data industry.

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.