MS Data Science

2 Years On Campus Masters Program

University of Maryland College Park

Program Overview

The University of Maryland's Master of Science in Data Science prepares students to transform complex datasets into meaningful insights through advanced statistical, computational and analytical techniques. Designed for working professionals, the 30-credit program combines probability, machine learning, big data systems, algorithms and data communication, helping graduates develop the expertise needed for data-driven decision-making, research and technological innovation.

Curriculum Structure

Year 1:
Students establish a strong foundation in data science through core courses covering mathematical principles, statistical analysis and computational techniques. Key subjects include DATA601 – Probability and Statistics, DATA602 – Principles of Data Science and DATA603 – Principles of Machine Learning. Students also study DATA604 – Data Representation and Modeling, developing the ability to organize, interpret and model complex datasets using modern analytical approaches.

Year 2:
Students advance their technical knowledge through courses focused on large-scale data processing, algorithms and professional communication. Core subjects include DATA605 – Big Data Systems, DATA606 – Algorithms for Data Science and DATA607 – Communication in Data Science and Analytics. Students complete an additional nine credits of approved electives, allowing them to explore specialized topics and strengthen their expertise in areas aligned with their professional interests. The program requires 30 credits and follows a non-thesis structure.

Focus Areas

Data Science, Probability and Statistics, Machine Learning, Big Data Systems, Data Representation and Modeling, Algorithms for Data Science, Data Mining, Network Analysis, Computational Methods, Statistical Analysis and Data Communication.

Learning Outcomes

Apply mathematical and statistical methods to complex datasets, develop and evaluate machine-learning models, design and implement data analysis solutions, understand big data systems and computational algorithms, organize and interpret data through appropriate modelling techniques, analyze networks and data streams, communicate analytical findings effectively, interpret statistical uncertainty and translate data-driven insights into informed decisions.

Professional Alignment (Accreditation)

The University of Maryland's Data Science program emphasizes practical and theoretical competencies required in modern data-driven organizations. Its curriculum integrates statistics, computer science, machine learning and professional communication, preparing students to conduct, interpret and communicate data analysis projects. Instruction is delivered by university faculty and industry experts through the College of Computer, Mathematical, and Natural Sciences. No separate professional accreditation is specified for the M.S. in Data Science on the official program page.

Reputation (Employability Rankings)

The University of Maryland, College Park is a leading public research university with strong academic and research capabilities across computing, mathematics and natural sciences. Through its College of Computer, Mathematical, and Natural Sciences, students benefit from an environment focused on scientific innovation, interdisciplinary research and advanced computational methods. The program's emphasis on machine learning, big data, statistical modelling and analytical communication prepares graduates for opportunities in data science, business analytics, machine learning, financial analytics, technology consulting and research.

Experiential Learning (Research, Projects, Internships etc.)

At the University of Maryland College Park, the MS in Data Science program is designed to provide students with hands-on experience that is crucial for success in the data-driven world. Students engage in practical learning through various projects, internships, and access to state-of-the-art facilities and tools. This experiential learning approach ensures that you not only understand theoretical concepts but also apply them in real-world scenarios, preparing you for a successful career in data science.

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

- Collaborative Projects: Engage in group projects that simulate real-world data challenges, allowing you to work alongside peers and faculty to solve complex problems.

- Internship Opportunities: The program encourages internships with industry partners, providing you with valuable work experience and networking opportunities.

- Advanced Software Tools: Gain proficiency in industry-standard software such as Python, R, SQL, and Tableau, which are essential for data analysis and visualization.

- Research Laboratories: Access dedicated research labs equipped with the latest technology for data analysis, machine learning, and artificial intelligence projects.

- Data Science Institute: Benefit from the resources and expertise of the Maryland Data Science Center, which fosters collaboration between students, faculty, and industry leaders.

- Field Trips and Workshops: Participate in field trips to tech companies and workshops led by industry experts, enhancing your understanding of current trends and practices in data science.

- Library Resources: Utilize the extensive resources available at the University Libraries, including databases, journals, and research materials specifically focused on data science.

Progression & Future Opportunities

The MS in Data Science at the University of Maryland College Park equips graduates with the skills and knowledge to excel in a rapidly growing field. Alumni have successfully transitioned into roles such as Data Scientist, Machine Learning Engineer, and Business Intelligence Analyst. With a strong foundation in data analysis and practical experience, graduates are well-prepared to meet the demands of the job market:

- University Services: The university offers dedicated career services, including resume workshops, interview preparation, and networking events specifically tailored for data science students. The Maryland Technology Enterprise Institute (Mtech) also provides resources for entrepreneurship and innovation.

- Employment Stats and Salary Figures: According to recent data, over 90% of graduates secure employment within six months of graduation, with starting salaries averaging around $100,000 per year, reflecting the high demand for data science professionals.

- University–Industry Partnerships: The University of Maryland has established partnerships with leading companies such as Amazon, IBM, and Lockheed Martin, providing students with internship opportunities and real-world 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 nationally.

- Graduation Outcomes: Graduates of the program have gone on to work at top-tier companies and have reported high job satisfaction, often advancing to leadership roles within a few years of entering the workforce.

Further Academic Progression: After completing the MS in Data Science, students have the option to pursue a Ph.D. in Data Science or related fields, which can open doors to academic positions, advanced research opportunities, and specialized roles in data analytics. Additionally, graduates may choose to obtain professional certifications in areas such as machine learning or artificial intelligence to further enhance their expertise and career prospects.