MSc in data science vs. MSc in computer science
Can't decide between a master's in data science or computer science? Learn about these two in-demand tech degrees and the career paths you can pursue after graduation.
By: Genevieve Carlton, Edited by: Rebecca Munday, Reviewed by: Monali Mirel Chuatico
Last updated: July 16, 2025
Earning a graduate degree in a tech field can lead to high-paying, in-demand career opportunities. Understanding the differences between a master's in data science and computer science, including focus areas, admission requirements, and career outcomes, can help you determine the right fit for your interests and career goals.
MSc in data science vs. MSc in computer science defined
Data science and computer science have significant overlaps and similarities. For example, professionals in both fields may work with artificial intelligence (AI). However, many schools separate the two subjects into different programs.
Data science is the study of how data is collected, organized, and analyzed.
Computer science is the study of computers and computational systems.
An MSc in computer science is typically a good choice if you want a career in computing or broader opportunities in areas such as:
- AI
- Computer systems and networks
- Security
- Programming languages
- Software engineering
However, if your goal is a role in data, like data engineer, machine learning engineer, or data analyst, an MSc in data science may be a better choice.
MSc data science vs. MSc computer science compared
While data science and computer science master's programs overlap in terms of cost and timeline, these two graduate tracks differ in their outcomes, curricula, and admission requirements. Learn more about the two options below.
| Factor | MSc data science | MSc computer science |
|---|---|---|
| Program outcomes | Graduates can pursue careers as data scientists, data analysts, machine learning engineers, and data architects. | Graduates can pursue careers as software developers, software engineers, cybersecurity engineers, and computer scientists. |
| Curriculum | Core courses include data science algorithms, data engineering principles, statistical methods, and machine learning. | Core courses include software engineering, computer architecture, network programming, and cybersecurity. |
| Cost | Costs vary widely depending on the number of credits required and the institution. The average cost of graduate tuition reached $20,500 in 2021-22. | Costs vary widely depending on the number of credits required and the institution. The average cost of graduate tuition was $20,500 in 2021-22. |
| Timeline | Data science master's programs typically take two years for full-time students. Some universities offer accelerated programs that take 1-1.5 years. | Computer science master's programs typically take two years for full-time students. Some universities offer accelerated programs that take 1-1.5 years. |
| Admission requirements | Bachelor's degree and prerequisite courses in calculus, advanced math, and computer programming | Bachelor's degree and prerequisite courses in calculus, advanced math, computer programming, data structures, and computer organization |
How to choose between an MSc in data science vs. an MSc in computer science
Getting a master's degree can advance your career, and it's critical to choose the right fit for your unique needs. When choosing between a master's in data science and a master's in computer science, consider your professional interests and your career goals.
A data science master's degree can help you strengthen your analytical and reasoning skills to manage complex data-driven projects. This degree program teaches advanced data mining, analysis, and visualization. It prepares you for careers in data science, data analysis, and machine learning.
In contrast, a computer science master's degree program enables students to develop computational and engineering skills, leading to diverse opportunities in software development, cybersecurity, and systems engineering.
Both master's programs offer tracks in machine learning, natural language processing, and artificial intelligence. Either degree can open career doors in the growing field of AI. Reviewing course requirements and concentration options can help you decide which degree is a better fit.
Computer science master's concentrations
Computer science master's concentrations include:
- Software engineering
- Artificial intelligence
- Cybersecurity
- Theoretical computer science
- Robotics
Data science master's concentrations
Data science master's concentrations include:
- Data analytics management
- Machine learning
- Artificial intelligence
- Data engineering
- Business intelligence
Get started on edX
Want to take the next step in your education? Apply to online master's in computer science and online master's in data science programs through edX.