Computer science vs data science: Which degree is right for you?

In terms of academic differences, computer science is a traditional degree which often sits in engineering departments. Study options are normally available at undergraduate, postgraduate and PhD and even professional diploma level depending on which university you choose to attend.    

The curriculum generally covers a wide range of topics, including, but not limited to, programming, algorithms, data structures, computer architecture, operating systems, artificial intelligence, software engineering, and cybersecurity.  

To enrol in a computer science degree, you will typically need strong math and problem-solving skills, along with a background in subjects like mathematics, physics, or computer science at the high school level. 

Data science, on the other hand, is a newer field, often available at the postgraduate level, though some universities now offer dedicated bachelor’s degrees and diplomas. These programmes are often housed in computer science, mathematics, or data science departments.  

The curriculum blends computer science, mathematics, and statistics, with core subjects like data mining, machine learning, statistical modelling, data visualisation, big data, and data ethics.  

Data science programmes often have more specialised entry requirements, typically seeking students with a solid foundation in mathematics, statistics, or a related quantitative discipline. 

While both subject areas require an aptitude for mathematics, it’s important to note that data science places a stronger emphasis on statistics. 

Both computer science and data science offer a variety of specialisations that allow students to tailor their studies to their interests and career goals.  

In computer science, specialisations may include: 

• Game design 

• Web development 

• Networking 

• Software engineering 

• Computer architecture 

• Artificial intelligence 

• Cybersecurity 

These electives enable students to dive deeper into specific aspects of computing, preparing them for a range of industries and roles. 

Data science, on the other hand, often offers more career-focused specialisations, providing students with the skills needed to tackle real-world challenges in fields like healthcare, finance, and business.  

Specialisations might include machine learning, big data, data visualisation, bioinformatics, and statistical modelling. These options allow students to develop expertise in using data to drive decision-making and innovation across various sectors. 

Both computer science and data science graduates can pursue a wide range of high-demand roles in the rapidly evolving tech sector. While there is some overlap, each field offers distinct career pathways that cater to different skill sets and interests. 

For computer science graduates, potential roles include: 

• Software engineer 

• Information security analyst  

• Web developer  

• Application/system developer  

• Games developer 

Data science graduates, on the other hand, are typically better suited for roles such as: 

• Data analyst 

• Data engineer 

• Data architect 

• Analytics manager 

• Statistician 

When choosing between the two subjects, make sure to consider your interests and career goals. If you enjoy designing robust systems, developing software, or solving technical challenges, a computer science degree may be a better fit.  

Alternatively, if you’re drawn to uncovering patterns, making data-driven decisions, and influencing strategy, data science could be the right path for you. 

Both fields offer competitive salaries and strong job security, reflecting the high demand for skilled professionals. Regardless of the path you choose, both degrees provide opportunities to innovate, solve complex problems, and drive meaningful change in a data-driven world. 

Here’s a quick of summary of what to consider before making your decision: