MS Data Science

1 Years On Campus Masters Program

Drexel University

Program Overview

Drexel’s Master of Science in Data Science (MSDS) is a 45-credit program that prepares students from diverse backgrounds to tackle very large, complex data sources, with a focus on data management, visualization and communication, and applied computational techniques. It suits students with strong undergraduate grades and technical skills, and you can study full-time or part-time, in Philadelphia or online, with an optional co-op for full-time on-campus students.

Curriculum Structure

Year 1: Building your data science foundation. You’ll start with DSCI 511 Data Acquisition and Pre-Processing and DSCI 521 Data Analysis and Interpretation, which teach you to collect, clean and interpret real data. Then you’ll move into the machine learning core with DSCI 631 Applied Machine Learning for Data Science, plus programming and quantitative foundations courses to fill in your skills. Full-time students on campus can prepare for co-op in their first fall through a short professional development course.

Year 2: Advanced modeling, the cloud and your capstone. You’ll take DSCI 632 Applied Cloud Computing and choose machine learning electives such as DSCI 641 Recommender Systems, Deep Learning or Natural Language Processing with Deep Learning. You can also earn up to three certificates, for example Big Data Analytics, HCI/UX Research and Design, or Applied AI/ML. You finish with the two-part capstone, DSCI 591 Data Science Capstone I and DSCI 592 Data Science Capstone II, where you apply your skills to a real-world data analysis task. Full-time students on the co-op plan complete a 6-month, full-time work experience in industry between their coursework and capstone II.

Focus Areas: Data acquisition and pre-processing, data analysis and interpretation, applied machine learning, cloud computing, recommender systems, visualization and communication of results, and data management and accountability.

Learning Outcomes: Graduates will be able to define and operationalize domain-specific data analysis hypotheses that generate meaningful insights, and select, transform and integrate data sources into solutions that scale to real-world deployment. They will implement reproducible and adaptable techniques for acquiring and developing data sets, and build, evaluate and apply analytical and predictive models to solve business problems. They will also visualize and interpret results and communicate them to stakeholders, and keep developing new skills that integrate computing with quantitative analysis and domain knowledge.

Professional Alignment (Accreditation): The MS is awarded by Drexel University, which is regionally accredited by the Middle States Commission on Higher Education. The program also builds professional alignment into its design through Drexel’s cooperative education model, which lets full-time on-campus students gain full-time work experience in data science. Graduates are prepared for careers in data architecture and infrastructure, predictive systems development, data and machine learning engineering, data analysis and statistics. Students work in the College of Computing & Informatics at 3675 Market Street, which has a Linux compute cluster, 12 GPUs and virtualization environments.

Reputation (Employability Rankings): U.S. News & World Report’s 2026 Best Colleges ranks Drexel 80th out of 434 universities, 41st among private universities, and No. 2 nationally for Co-ops/Internships. These are university-wide rankings, not rankings of the MSDS itself, and the co-op ranking is the standout for career outcomes. The co-op option is available to full-time, on-campus students only, so it’s worth highlighting for applicants who plan to study in Philadelphia.

Experiential Learning (Research, Projects, Internships etc.)

At Drexel University, the MS in Data Science program is designed to provide students with hands-on experience that is essential for success in the rapidly evolving field of data analytics. Students engage in practical learning through a combination of collaborative projects, internships, and access to cutting-edge facilities and tools. This experiential learning approach ensures that graduates are not only knowledgeable but also equipped with the skills needed to tackle real-world challenges.

Here are some key aspects of the experiential learning opportunities available in the MS Data Science program at Drexel:

- Collaborative Projects: Students work on team-based projects that simulate real-world data science challenges, allowing them to apply theoretical knowledge in practical settings.

- Internships: The program encourages students to participate in internships with industry partners, providing invaluable experience and networking opportunities.

- State-of-the-Art Facilities: Students have access to advanced computing labs equipped with the latest software and hardware necessary for data analysis and machine learning.

- Software Tools: The curriculum includes training in popular data science tools and programming languages such as Python, R, SQL, and Tableau, ensuring students are proficient in industry-standard technologies.

- Research Opportunities: Students can engage in research projects through various institutes and labs, such as the Drexel Data Science Institute, which focuses on innovative data-driven solutions.

- Field Trips and Industry Visits: The program often includes field trips to local tech companies and organizations, giving students insight into how data science is applied in various sectors.

- Library Resources: The Drexel Libraries provide access to a wealth of academic resources, databases, and journals that support research and learning in data science.

Progression & Future Opportunities

Drexel University's MS in Data Science program equips graduates with the skills and knowledge needed to excel in a rapidly evolving field. With a strong emphasis on practical experience and industry collaboration, students are well-prepared for roles such as Data Analyst, Data Scientist, and Machine Learning Engineer. The demand for data professionals continues to grow, making this an exciting time to enter the field:

- University Services: Drexel offers robust career services, including resume workshops, interview preparation, and networking events with industry leaders. The Steinbright Career Development Center provides co-op opportunities that allow students to gain real-world experience while earning academic credit.

- Employment Stats and Salary Figures: According to recent data, over 90% of Drexel graduates secure employment within six months of graduation, with starting salaries averaging around $85,000 for data science roles.

- University–Industry Partnerships: Drexel has established partnerships with leading companies such as Comcast, SAP, and Lockheed Martin, providing students with access to internships and collaborative projects that enhance their learning experience.

- Long-term Accreditation Value: The program is accredited by the Middle States Commission on Higher Education, ensuring that the education you receive meets high standards and is recognized by employers.

- Graduation Outcomes: Graduates of the MS in Data Science program have gone on to work at top firms in various sectors, including finance, healthcare, and technology, demonstrating the versatility and demand for their skills.

Further Academic Progression: After completing the MS in Data Science, students have the opportunity to pursue a PhD in Data Science or related fields, allowing them to delve deeper into research and contribute to advancements in the discipline. Additionally, graduates can explore certifications in specialized areas such as machine learning or artificial intelligence, further enhancing their expertise and career prospects.