Strengthen Your Data Science Skills. Advance Your Career.
WPI's pioneering Master of Science in Data Science online program prepares you to derive new insights from data and articulate these findings into innovative solutions for how we live, work, and interact with the world around us.
Equipped with this degree, you’ll master database management and analysis techniques such as machine learning and data-mining algorithms. You’ll also gain a deeper knowledge of statistics and will have used a rich diversity of data-analysis software. WPI’s interdisciplinary approach rounds out your degree while developing your interpersonal and storytelling skills alongside technical mastery. In 2022, Fortune magazine ranked WPI fifth in their list of Best Online Master’s in Data Science Programs.
In addition to core courses that teach data science essentials, you’ll can customize the program with specializations in Artificial Intelligence (AI) & Machine Learning or Big Data. As an added benefit, built-in bridge courses mean there is no specific undergraduate degree needed for admission—and the GRE is not required.
- Deepen your skills in cutting-edge AI courses on deep learning, machine learning, reinforcement learning, social media analytics, natural language processing—including ChatGPT—and more
- Use industry-leading tools including Pytorch, MySQL, Python, Matlab, and more
- Learn from world-class faculty who are scholarly and industry leaders in their fields
- Work on real-world projects that are industry-supported and industry-mentors—equipping you with experience to secure a professional role (or advance an existing one)
- Take advantage of bridge courses which allows for no specific undergraduate degree to enroll
- Go beyond an MS degree with one-on-one directed studies or prepare to eventually pursue a PhD
No application fees or GRE required!
This program is also available on campus
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Curriculum for Master of Data Science Online
The Master of Science in Data Science program online begins with a foundational track required for students without appropriate math and/or programming experience. After completing core courses, students can choose from three specializations in Artificial Intelligence (AI) & Machine Learning, Big Data Analytics & Management, or Business Intelligence.
Make the Most of Your WPI Experience
- Current WPI students, even those whose undergraduate degree is not in computer science, may explore a BS/MS program option to gain both degrees in an accelerated plan.
Program Requirements
The online data science degree requires the completion of 30 graduate credit hours. The distribution of credits is as follows:
Integrative Data Science (3 credits)
Mathematical Analytics (3 credits)
Data Access and Management (3 credits)
Data Analytics and Mining (3 credits)
Business Intelligence and Case Studies (3 credits)
Electives (12 credits)
*No more than 14 credits of the total 30 credit hours for this degree may be courses offered by the School of Business.
Graduate Qualifying Project (GQP) (3 credits)
Courses
Integrative Data Science (3 credits)
- DS 501: Introduction to Data Science
Mathematical Analytics (3 credits)
- DS 502/MA 543 Statistical Methods for Data Science
Data Access and Management (3 credits)
(Choose one of the suggested courses below)
- CS 542 Database Management Systems
- MIS 571 Database Applications Design and Development
- CS 585/DS 503 Big Data Management
Data Analytics and Mining (3 credits)
(Choose one of the suggested courses below)
- CS 548 Knowledge Discovery and Data Mining
- CS 539 Machine Learning
- CS 586/DS 504 Big Data Analytics
Business Intelligence and Case Studies (3 credits)
- MIS 584 Business Intelligence
Electives (12 credits)
Student will consult with their Academic Advisor to select courses to fufill this requirement.
Graduate Qualifying Project (GQP) (3 credits)
- DS598 Graduate Qualifying Project
To find the next offering of online Data Science courses, visit the Registrar’s site.
To view a course description, visit the Graduate Catalog.
Subject to change based on availability.
What Can I Do with a Master’s in Data Science?
Data Scientist
- 15% job growth from 2019 to 2029
-
$122,840 national average salary
In-demand skills:
-
Distributed computing
-
Predictive modeling
-
Math, stats, machine learning
Source: U.S. Bureau of Labor Statistics
Data Analyst
- 6% job growth from 2019 to 2029
-
$88,550 national average salary
In-demand skills:
-
Spreadsheet tools
-
Database systems
-
Communication & visualization
Data Architect
-
10% job growth from 2019 to 2029
-
$97,350 national average salary
In-demand skills:
-
Data warehousing solutions
-
Database architecture
-
Systems development
Data Engineer
-
10% job growth from 2019 to 2029
-
$93,750 national average salary
In-demand skills:
-
Database systems
-
Data modeling & ETL tools
-
Data APIs
Business Analyst
-
7% job growth from 2019 to 2029
-
$90,920 national average salary
In-demand skills:
-
Data visualization tools
-
Business intelligence
-
Data modeling
Database Administrator
-
10% job growth from 2019 to 2029
-
$93,750 national average salary
In-demand skills:
-
Backup & recovery
-
Data modeling & design
-
Database systems
Alumni
Meet Our DS Graduates
DS Meet Our Alumni.
Chenjie Jiang, Data Scientist at Burning Glass
The high flexibility for course selections gave me a strong background in data science, engineering, and business. I can create my own learning path, based on my career plan. The program also offers interesting colloquium and conversations. WPI is a good place if someone wants to dive into the data science world.
Yao-Chun Hsieh, Software Engineer at Wayfair
DS 501 taught by Professor Paffenroth is one of the best courses I have taken at WPI.
The curriculum is flexible and provides students the opportunity to grow their skills based on their interest or their ideal job.
You also learn ways of communicating with your teammates, dealing with conflicts, and schedule/time management skills. All of this helped me to fit into the real world quickly and smoothly.
Yang Tao, Retail marketing team, strategy & operation analyst, contractor for Google
During my course of study, I could choose different classes in areas like AI, machine learning, Big Data, and business intelligence. I learned database (sql), data processing and analysis (python), data reporting (tableau). Each course benefited me during my job hunting, as I talked about my projects in the different courses to match different roles and job descriptions. Through my graduate qualifying project (capstone), I also learned new techniques/methods/software to solve data related problems, while improving my public speaking and communication skills.
Alexander Shoop, Software Engineer at DataRobot
The Data Science graduate program has taught me the necessary fundamentals of machine learning and pragmatic data science projects through teamwork. Personally, it has also allowed me to use my creative talent, especially with regards to presentations and video demonstrations. I would absolutely recommend the Data Science program (undergraduate, graduate, and PhD) to any of my friends and colleagues! The program emphasizes team collaboration and working towards having a diverse skill set to handle any kind of data science scenario.
Mukund Khandelwal, Quantitative Associate at Wells Fargo
The overall graduate experience involved collaborating with students coming from different academic and cultural backgrounds. Through this experience, I learned how a problem could be approached from multiple angles and solved effectively.
Chen Liang, Data Scientist at Burning Glass
This program starts from a fundamental base and keeps upgrading the difficulty, which made me comfortable and built up my confidence and enhanced my skills—and ultimately made me ready to walk into my new job. It has provided such a great way to not only get our hands dirty real quick, but allows us to innovate.
Rosemarie Day, Senior Engineer in Applied Data Science at Collins Aerospace
I greatly enjoyed the GQP, which connected me with a company and a project that I could interact with and develop while finishing my degree. The project work allowed me to grow my skills in more of a corporate environment while still in school. This provided me with insights into how a data science team works outside of the classroom, what expectations would be set, and also allowed me to work alongside both other students and industry professionals.
Xiao-Qun Wang, Software Development Engineer at Amazon
I learned the data eco-system from both academic and industrial perspective in the Data Science program. The graduate qualifying project (capstone) gave me exposure in industry. It not only helped me to learn the foundation of industrial core tech, but also how to build good relationships both with the company and other developers.
Chenjie Jiang, Data Scientist at Burning Glass
The high flexibility for course selections gave me a strong background in data science, engineering, and business. I can create my own learning path, based on my career plan. The program also offers interesting colloquium and conversations. WPI is a good place if someone wants to dive into the data science world.
Yao-Chun Hsieh, Software Engineer at Wayfair
DS 501 taught by Professor Paffenroth is one of the best courses I have taken at WPI.
The curriculum is flexible and provides students the opportunity to grow their skills based on their interest or their ideal job.
You also learn ways of communicating with your teammates, dealing with conflicts, and schedule/time management skills. All of this helped me to fit into the real world quickly and smoothly.
Yang Tao, Retail marketing team, strategy & operation analyst, contractor for Google
During my course of study, I could choose different classes in areas like AI, machine learning, Big Data, and business intelligence. I learned database (sql), data processing and analysis (python), data reporting (tableau). Each course benefited me during my job hunting, as I talked about my projects in the different courses to match different roles and job descriptions. Through my graduate qualifying project (capstone), I also learned new techniques/methods/software to solve data related problems, while improving my public speaking and communication skills.
Alexander Shoop, Software Engineer at DataRobot
The Data Science graduate program has taught me the necessary fundamentals of machine learning and pragmatic data science projects through teamwork. Personally, it has also allowed me to use my creative talent, especially with regards to presentations and video demonstrations. I would absolutely recommend the Data Science program (undergraduate, graduate, and PhD) to any of my friends and colleagues! The program emphasizes team collaboration and working towards having a diverse skill set to handle any kind of data science scenario.
Mukund Khandelwal, Quantitative Associate at Wells Fargo
The overall graduate experience involved collaborating with students coming from different academic and cultural backgrounds. Through this experience, I learned how a problem could be approached from multiple angles and solved effectively.
Chen Liang, Data Scientist at Burning Glass
This program starts from a fundamental base and keeps upgrading the difficulty, which made me comfortable and built up my confidence and enhanced my skills—and ultimately made me ready to walk into my new job. It has provided such a great way to not only get our hands dirty real quick, but allows us to innovate.
Rosemarie Day, Senior Engineer in Applied Data Science at Collins Aerospace
I greatly enjoyed the GQP, which connected me with a company and a project that I could interact with and develop while finishing my degree. The project work allowed me to grow my skills in more of a corporate environment while still in school. This provided me with insights into how a data science team works outside of the classroom, what expectations would be set, and also allowed me to work alongside both other students and industry professionals.
Xiao-Qun Wang, Software Development Engineer at Amazon
I learned the data eco-system from both academic and industrial perspective in the Data Science program. The graduate qualifying project (capstone) gave me exposure in industry. It not only helped me to learn the foundation of industrial core tech, but also how to build good relationships both with the company and other developers.
Chenjie Jiang, Data Scientist at Burning Glass
The high flexibility for course selections gave me a strong background in data science, engineering, and business. I can create my own learning path, based on my career plan. The program also offers interesting colloquium and conversations. WPI is a good place if someone wants to dive into the data science world.
Manasi Vartak '10.
Manasi Vartak '10 founded Verta to help companies build AI-enabled products faster than ever.
Meet Our Faculty
I completed my Ph.D. in Information Technology from the Department of Computer Science at George Mason University. Before that, I received MBA in Management Information Systems from California State University, Chico and BEng in Electronic Engineering from the Hong Kong University of Science and Technology respectively. My teaching interests include Database Management Systems, Data Mining, Artificial Intelligence, Machine/Deep Learning, Data Analytics, Decision Support System, Data Structures, Computational Algorithms, and Software Application Programming.
As founding Head of the interdisciplinary Data Science program here at WPI, I take great pleasure in doing all in my power to support the Data Science community in all its facets from research collaborations, and new educational initiatives to our innovative industry-sponsored and mentored Graduate Qualifying projects at the graduate level.
I enjoy teaching because it allows me to interact with students who have the potential to make the world a better place using technology. I continually innovate in my courses to ensure students enjoy the learning experience, learn the key concepts and skills related to information systems through real world examples, have an opportunity to learn from each other, learn to present themselves as professionals, and most importantly learn to use or develop technology to make a difference.
Seyed A. (Reza) Zekavat received his PhD from Colorado State University in 2002. He is the Author of the textbook "Electrical Engineering: Concepts and Applications" published by Pearson, and the editor of the book “Handbook of Position Location: Theory, Practice and Advances,” published by Wiley/IEEE. He holds a patent on an active Wireless Remote Positioning System.
I completed my Ph.D. in Information Technology from the Department of Computer Science at George Mason University. Before that, I received MBA in Management Information Systems from California State University, Chico and BEng in Electronic Engineering from the Hong Kong University of Science and Technology respectively. My teaching interests include Database Management Systems, Data Mining, Artificial Intelligence, Machine/Deep Learning, Data Analytics, Decision Support System, Data Structures, Computational Algorithms, and Software Application Programming.
As founding Head of the interdisciplinary Data Science program here at WPI, I take great pleasure in doing all in my power to support the Data Science community in all its facets from research collaborations, and new educational initiatives to our innovative industry-sponsored and mentored Graduate Qualifying projects at the graduate level.
I enjoy teaching because it allows me to interact with students who have the potential to make the world a better place using technology. I continually innovate in my courses to ensure students enjoy the learning experience, learn the key concepts and skills related to information systems through real world examples, have an opportunity to learn from each other, learn to present themselves as professionals, and most importantly learn to use or develop technology to make a difference.
Seyed A. (Reza) Zekavat received his PhD from Colorado State University in 2002. He is the Author of the textbook "Electrical Engineering: Concepts and Applications" published by Pearson, and the editor of the book “Handbook of Position Location: Theory, Practice and Advances,” published by Wiley/IEEE. He holds a patent on an active Wireless Remote Positioning System.
I completed my Ph.D. in Information Technology from the Department of Computer Science at George Mason University. Before that, I received MBA in Management Information Systems from California State University, Chico and BEng in Electronic Engineering from the Hong Kong University of Science and Technology respectively. My teaching interests include Database Management Systems, Data Mining, Artificial Intelligence, Machine/Deep Learning, Data Analytics, Decision Support System, Data Structures, Computational Algorithms, and Software Application Programming.
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