B.Sc in Computer Science Vs B.Sc in Data Science: Which is Right for You?

Are you a fan of Iron Man, or is Captain America your sweetheart? It’s difficult to choose between the two popular superheroes from the same Marvel Universe, isn’t it? One is too spectacular to miss out on, and the other might interest you the most. Similarly, a BSc in Computer Science and a BSc in Data Science are like two knights of the tech world. Selecting the right one for yourself might be too baffling.

However, just like Iron Man is known for his intelligence, a BSc in Computer Science is popular for offering a vast career full of opportunities. On the other hand, a BSc in Data Science allows you to enter a world of unfathomable innovation similar to Captain America’s unbeatable strategies. The potential, offerings, and career prospects of both are spectacular. So, how do you choose the right one?

This blog would dive deeply into a detailed analysis of BSc in Computer Science vs BSc in Data Science. Let’s discover some secrets of both specialisations and their pros and cons. So, are you ready to dive in? Let’s get into it!

Explore BSc: Computer Science vs Data Science

BSc, or Bachelor of Science, is a science-focused course, whether computer, data, biology, physics, or environment. It’s a three-year undergraduate degree, which offers you a range of specialisations to choose from. Since a BSc is one of the most popular courses for science specialisations, it’s easier to find top colleges.

Moving on, computer science and data science are the two specialisations offered in the BSc programme. Often misinterpreted with each other, it becomes difficult to understand the difference between both. Even though data science may sound like a subset of computer science, it’s a majestic field.

With a BSc in Data Science, you could pursue a career in automation and innovation, such as AI and machine learning. However, you can explore an exceptional software and information technology world with a BSc in Computer Science. Sounds fascinating, right? But it’s equally confusing as well. So, let’s move further to shed light on the potential outcomes of computer science and data science.

Also Read: BSc Explained: Full Form, Specialisations, Colleges and more

Computer Science or Data Science: What’s the Difference?

When computer science was enjoying its fandom and popularity among tech enthusiasts, data science stepped into the kingdom. As a newbie to the world of science, it has behaved like an introvert and followed the steps of computer science. It took years to establish, but “Actions speak louder than words.”

Data science became popular when AI became the talk of the town. It has significantly contributed to the data-driven world and is integral to artificial intelligence. However, even with immense popularity and a rich yet young career scope with possibilities of rapid advancement in the upcoming years, it couldn’t replace computer science. So, who won the throne of the tech world? Well, this might sound a bit disappointing to you because it has yet to be made clear.

However, here comes the beauty of the tech realm. Like the Avengers, Iron Man and Captain America are superheroes, but they work together as a team instead of being in opposition. Similarly, computer science and data science work together to improve the world with technological advancements. Where computer science focuses on IT and software development to enhance user interface and user experience, data science uses data to make things easier for users. Here is a quick analysis of the difference between computer science and data science:

Also read: Online MBA vs. Online MCA in Data Analytics: Which Degree is Right for You?

From Algorithms to Analytics: Understand Curriculum

BSc in Computer Science

It is a bachelor’s degree programme emphasising CS-specific concepts. Enrolling in this specialisation gives you a different perspective on computers. It allows you to view computers as part of science. It provides you with knowledge of computer architecture, including hardware and software. Being an undergraduate with a BSc in Computer Science, here are several core subjects that you would study:

BSc in Data Science

It is a UG programme of 3 years. With data science as your specialisation in your BSc, you would learn computational mathematics, data analytics, and the impacts of data-driven technologies from a future perspective. The following are some fundamental subjects offered in the BSc in Data Science:

Also Read: What Is Data Science & Where It Is Used? Learn Here

Skills Comparison: Which Makes You Unique?

Computer science and data science skills go hand in hand. Whether a computer architect or data scientist, your skills would overlap. However, although both roles share too many common skills, most skills are used separately.

Furthermore, skills like data organisation and programming languages are common in both data science and computer science. However, both disciplines also emphasise a specific set of skills, which distinguish them. The following is a brief description of the unique skills of individuals in data science and computer science.

Skills in BSc in Computer Science

Skills in BSc in Data Science

Career Outlook: How Far Would You Go?

Picture this: You have two options: either you could be a data scientist or a computer scientist. You are too confused to choose the right one. You have considered both the programmes, their curriculums, and even their skills. So, what’s still left that you must consider before choosing the right career path? It’s the career outlook and scope of a specific field or role. Let’s understand the career outlook for computer science and data science.

According to the US Bureau of Labour Statistics (2024), the job outlook is projected to grow by 26%. This is a much faster rate than the average estimated between 2023 and 33. This simply signifies that computer science offers a robust career with a vast scope.

On the other hand, data scientists’ projected growth rate is 36% between 2023 and 33. It’s a rapid increase in the rate estimated within a decade. Moreover, US BLS (2024) only mentions 202,900 job openings in 2023.

As per estimated growth rates, both careers are skyrocketing. Enrolling in any of these specialisations could bring you lots of career opportunities. Career growth in data science might seem more likely, but both are rapidly emerging careers with no signs of downfall. Here are some career prospects along with the average salary in both courses that you might consider:

Also Read: Spreadsheet Superstar: Your Path to Data Analyst Domination

Money Matters: Salary Prospects

There would always be two exciting segments for every new job on induction day. The first is how many paid leaves you could take annually. The other is when your salary would be credited. Agree? So, when choosing between a BSc in Computer Science and a BSc in Data Science, you must first consider its career outlook. And we have already sorted that part.

So, here comes the salary part, which is part of understanding how much you could earn in the future. In India, you could earn an average of INR 3.8 LPA to INR 28 LPA as a data scientist. However, being a computer scientist with 2-10 years of experience, INR 20 LPA – INR 70 LPA is an average pay scale. Furthermore, average salary ranges often vary based on location, experience, and skills.

For instance, the median pay for data scientists in the US was $ 108,020 (INR 91,16,658.11) in 2023. On the other hand, it was $ 145,080 for computer scientists, nearly equal to INR 1,22,44,443.24. According to salary prospects, both careers offer a handsome pay scale. Moreover, depending on your location, it can significantly vary.

Final Showdown: Iron Man’s Intelligence or Captain America’s Strategies

Have you ever wondered if Iron Man had to fight with Captain America? Then, the battle might have never ended. BSc in Computer Science and BSc in Data Science are exactly like them. Both have incredible qualities, offer great curricula, and provide impressive career outlooks and salary prospects. You need to choose the right one based on your interests and requirements. Here is a quick recap:

BSc in Computer Science:

• Overview: Emphasises computational theory, programming, and system design.

• Core subjects: data structures, operating systems, networking, AI, and software engineering.

• Skills: programming, problem-solving, and database management.

• Tools & Tech: C/C++, Java, Linux, Git, and SQL.

• Career Opportunities: Software engineer, system analyst, and web developer.

• Job Potential: High-in-demand among IT sectors.

• Future Learning Options: MSc in Computer Science, MCA, or MBA in Computer-Based Specialisations.

• Challenges: prolonged coding and complicated algorithms.

• Industry Demand: IT, software, telecommunications, and government agencies.

• Ideal for Students Who? If you enjoy coding and understand system architecture.

BSc in Data Science:

• Overview: Focuses on data analysis, machine learning, and statistics.

• Core Subjects: Machine learning, data mining, data visualisation, and statistics.

• Skills: data interpretation, analytical thinking, and statistical analysis.

• Tools & Tech: Python, R, SQL, Tableau, and Hadoop.

• Career Opportunities: Data scientist, data analyst, and machine learning engineer.

• Job Potential: Data-driven field in tech, healthcare, and finance industries.

• Future Learning Options: MSc in Data Science or Data Analytics, MCA in AI, MBA in AI or Data Analytics.

• Challenges: advanced statistical concepts and continuously evolving data science.

• Industry Demand: Tech, finance, and healthcare.

• Ideal for Students Who? If you are passionate about statistics and can derive significant data insights.

Also Read: Online BSc In Computer Science: Fee, Course, Admission, Colleges, Scope

Takeaway: How to Choose the Best

BSc in Computer Science and BSc in Data Science are excellent courses. Both offer a great curriculum, career prospects, and salary outlook. They both share most skills, like programming. So, let’s make choosing the right programme for you simple. All you need to do is follow a quick process.

In this process, you figure out your interests, like the subjects you enjoy doing the most. Then, discover your strengths and the field in which you can excel. The rest of the process includes researching the career outlook and curriculum of the specialisation, which has already been done. Moreover, you must choose the specialisation that aligns with your interests and strengths.