Data Science MS

2 Years On Campus Masters Program

De Paul University

Program Overview

The Master of Science in Data Science at DePaul University prepares students to solve complex data challenges by combining advanced computational techniques, statistical analysis, machine learning, and artificial intelligence. Offered through the Jarvis College of Computing and Digital Media, the programme develops practical skills in managing large datasets, building predictive models, interpreting analytical results, and designing responsible AI solutions. Students can specialize in Computational Methods, Health Care, or Marketing, preparing for careers across technology, healthcare, business analytics, and research. The programme is STEM-designated and offers flexible online, on-campus, and hybrid study options.

Curriculum Structure

The programme requires a minimum of 48 graduate credit hours, with additional introductory courses (up to 12 credit hours) depending on the student's academic background. Most full-time students complete the degree in 18–24 months. The curriculum combines foundational data science subjects, advanced technical coursework, and concentration-specific electives.

Year 1:

During the first year, students establish a strong foundation in programming, statistical analysis, data management, and data science methodologies. Core subjects include Fundamentals of Data Science (DSC 441), Python Programming (DSC 430), Data Visualization (DSC 465), and Database Processing for Large-Scale Analytics (DSC 450). Students also study Machine Learning I (DSC 445), Applied Deep Learning (CSC 483), and Ethics in Artificial Intelligence (CSC 484), developing the ability to process complex datasets, build machine learning models, and understand responsible AI applications.

Year 2:

During the second year, students advance their technical expertise through specialized courses and concentration-based electives. Subjects include Programming Machine Learning Applications (DSC 478) and Mining Big Data (CSC 555), which strengthen their abilities in predictive modelling, large-scale data processing, and advanced analytics. Depending on their chosen concentration, students can explore additional areas such as advanced modelling, image processing, healthcare analytics, or marketing analytics. This flexible structure allows students to develop expertise aligned with their intended professional career.

Focus Areas

Data Science, Computational Methods, Statistical Analysis, Machine Learning, Deep Learning, Artificial Intelligence, Python Programming, Data Visualization, Database Management, Big Data Analytics, Predictive Analytics, Data Mining, Data Processing, Advanced Statistical Modelling, Healthcare Analytics, Clinical Data Analytics, Marketing Analytics, Customer Relationship Management, Business Intelligence, Data Engineering, Responsible AI, Algorithmic Analysis, Data Interpretation, Computational Analysis.

Learning Outcomes

Develop and evaluate predictive models using statistical, machine learning, and deep learning techniques, manage and analyse large and complex datasets, apply Python programming and computational methods to data science problems, perform data preparation, normalization, and reduction, implement data visualization techniques to communicate analytical findings, design and evaluate machine learning solutions, apply advanced data science methods to healthcare and marketing challenges, interpret AI-generated outputs and identify potential model limitations, conduct independent data science investigations, apply ethical reasoning to artificial intelligence applications, develop data-driven solutions for business and organizational challenges, and communicate technical findings effectively to non-technical audiences.

Professional Alignment (Accreditation)

The Master of Science in Data Science is offered through DePaul University's Jarvis College of Computing and Digital Media and is a STEM-designated programme. Its curriculum emphasizes industry-relevant competencies in programming, machine learning, artificial intelligence, statistical modelling, database management, and large-scale data analytics. Students gain practical experience through project-based coursework, specialized research laboratories, and opportunities to collaborate on real-world data science challenges. The programme does not specify a separate external professional accreditation on its official programme page.

Reputation (Employability Rankings)

DePaul University highlights strong career opportunities for Data Science graduates across technology, healthcare, consulting, finance, retail, and business analytics. According to the university's 2025 programme prospectus, 93% of Data Science MS graduates were employed, continuing their education, or pursuing other goals within six months of graduation.

Graduates have secured opportunities with organizations such as Amazon, Meta, BMW, Apple, Deloitte, Google, CVS, Walgreens, CME Group, Discover Financial Services, and Microsoft. Potential career pathways include Data Scientist, Machine Learning Engineer, Applied Scientist, Analytics Manager, and Data Engineer. The university also highlights the programme's national recognition for its combination of academic quality and affordability. No specific QS or Guardian programme-level employability ranking is listed on the official programme page.

Experiential Learning (Research, Projects, Internships etc.)

At DePaul University, the Data Science MS program is designed to provide students with hands-on experience that bridges the gap between theory and practice. Students engage in real-world projects, utilize cutting-edge technology, and collaborate with peers to solve complex data challenges. The program emphasizes experiential learning through various opportunities, ensuring that graduates are well-prepared for the demands of the data science field.

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

- State-of-the-Art Facilities: Access to advanced computer labs equipped with high-performance computing resources and software tools essential for data analysis and machine learning.

- Software Proficiency: Students gain experience with industry-standard software such as Python, R, SQL, and Tableau, which are integral to data manipulation and visualization.

- Collaborative Projects: Engage in group projects that simulate real-world data science scenarios, allowing students to work together to analyze data sets and present findings.

- Internship Opportunities: The program encourages internships with local companies and organizations, providing students with valuable industry experience and networking opportunities.

- Research Laboratories: Access to dedicated research labs where students can work on innovative projects, often in collaboration with faculty members who are experts in the field.

- Field Trips and Industry Visits: Opportunities to visit local tech companies and data-driven organizations, giving students insight into the practical applications of their studies.

- Libraries and Resources: Utilize DePaul’s extensive library system, which includes access to a wealth of academic journals, databases, and resources specific to data science research.

- Institute Collaborations: The program often collaborates with various institutes and centers within the university, providing students with additional resources and expertise.

These experiential learning components are designed to enhance your educational journey and prepare you for a successful career in data science.

Choosing the Data Science MS program at DePaul means you’re not just learning; you’re actively engaging with the data science community and building the skills you need to thrive in your future career.

Progression & Future Opportunities

Pursuing a Master’s in Data Science at DePaul University opens up a world of opportunities for graduates. With a strong emphasis on practical skills and real-world applications, students can expect to step into roles such as Data Analyst, Data Scientist, Machine Learning Engineer, or Business Intelligence Analyst. The demand for data professionals continues to grow, making this program a strategic choice for your future career.

Here’s how DePaul supports your journey toward success:

- Career Services: DePaul offers dedicated career services, including resume workshops, interview preparation, and networking events tailored specifically for data science students.
- Employment Statistics: Graduates from the Data Science MS program have reported a high employment rate, with many securing positions within six months of graduation. The average starting salary for data science roles in the Chicago area is around $85,000, with potential for growth as you gain experience.
- University–Industry Partnerships: DePaul has established partnerships with leading companies such as Accenture, Deloitte, and Allstate, providing students with internship opportunities and real-world projects that enhance learning and employability.
- Accreditation Value: The program is accredited by the Higher Learning Commission, ensuring that your degree holds value in the job market and meets high educational standards.
- Graduation Outcomes: Alumni of the program have gone on to work at top tech firms, financial institutions, and healthcare organizations, showcasing the versatility and demand for data science skills.

Further Academic Progression: After completing your Master’s in Data Science, you may choose to further your studies by pursuing a Ph.D. in Data Science or a related field. This could lead to advanced research opportunities or academic positions, allowing you to contribute to the evolving landscape of data science and analytics. Additionally, you might consider certifications in specialized areas such as machine learning or artificial intelligence to enhance your expertise and career prospects.

Choosing DePaul for your graduate studies in Data Science is not just about earning a degree; it’s about building a future filled with possibilities.