Data science is one of the hottest growing industries in the information and technology field, with applications in almost every industry. As big data continues to grow, so will the need for professionals able to make sense of this data. The U.S. Bureau of Labor Statistics projects a 16% growth in job opportunities through 2028, much faster than the average for all occupations.
Whether you are looking to gain data analytics knowledge to enhance your current role or seeking a career change, our new Master of Science in Data Science (MSDS) program will provide you with the skills, perspective and expertise to succeed in today’s rapidly changing, information and technology driven economy.
Drawing on the interdisciplinary strengths of Drexel’s College of Computing & Informatics (CCI), the 45-credit MS in Data Science program provides students with in-depth knowledge of core data science principles and the origin of tools necessary to harness big data.
Graduates of the MS in Data Science program are able to collect, manage and analyze massive, “noisy,” and fast-growing datasets within complex systems, which can lead to unique discoveries and insights, and create values for a variety of domains, including healthcare, finance and/or business operations.
Data Science Masters Bootcamp
Are you interested in learning more about data science or CCI's master's in data science program? Attend one of our free, virtual, two-day Master's in Data Science Bootcamp sessions on Aug. 29 & 30, 2020, and/or Sept. 19 & 20, 2020.
Data Science Master Program Features
- Dynamic, interdisciplinary program taught by world class faculty from CCI's information science and computer science departments
- Completing our graduate program in Data Science provides a strong foundation, and a self-directed specialization through the application of data science methods, development of computational tools and algorithms, and management of data and information to solve data-centric problems, gain insights and communicate them to diverse audiences
- Designed for students with or without a bachelor’s degree in Data Science
- Curriculum emphasizes data science concepts in three concentrated areas: 1) Analytics, Mining and Algorithms; 2) Visualization and Communication; and 3) Management and Accountability
- Students choose electives from within the above concentrated areas to gain hands-on experience in the area of computation, and work with state-of-the-art tools and systems to analyze real datasets
- Capstone project gives MSDS students the opportunity to gain practical, real-world industry experience within their area of interest, and use their new knowledge before graduation
- Students have the option to pursue a dual degree program combining the MS in Data Science with any other CCI graduate program
Data Science Graduate Program Goals (Key Learning Outcomes)
- Analyze a problem and identify and define the data analysis, computing and result presentation requirements appropriate to its solution.
- Interpret and communicate the output of statistical and algorithmic methods.
- Function effectively on a team to design and implement a computer-based data analysis system.
- Harvest, collect, and integrate diverse data to produce valued project resources.
- Understand the implementation and use of existing data science tools and systems.
Data Science Masters Program Overview
CCI's masters degree in Data Science is a 45-credit program, consisting of four required courses and 11 electives, drawing from three tracks (Analytics, Mining and Algorithms; Visualization and Communication; and Management and Accountability).
Complete Your Data Science Masters Degree:
- On Campus
- A completed application.
- A four-year bachelor's degree from a regionally accredited institution in the United States or an equivalent international institution.
- Those without a prior degree or sufficient work experience in Computer Science, Software Engineering, or Math (plus programming) may have to take additional prerequisites before pursuing advanced computer science courses.
- A GPA of 3.0 or higher, in a completed degree program, bachelor’s degree or above.
- Provisional Admission is not available with this program
- Official final transcripts from ALL Colleges/Universities attended.
- Graduate Record Examination (GRE) Scores are not required.
- One letter of recommendation required, two recommended (academic, professional, or both).
- Essay/Statement of Purpose: In approximately 500 words, describe what professional goals you hope to achieve, how an advanced degree facilitates that success and anything else you want the Admissions Review Board to know about you.
- Current Resume.
- Additional requirements for International Students.
- Visit our Graduate Admissions section for application deadlines.
Graduate Co-Op Program Available
Cooperative education at Drexel is now available for the full time MS in Data Science degree program. Graduate Co-op enables graduate students to alternate class terms with a six-month period of hands-on experience, gaining access to employers in their chosen industries.
Learn more at drexel.edu/scdc/co-op/graduate
Master of Data Science Program Course Requirements & Descriptions
Please visit Drexel's Graduate Catalog for course requirements and a sample plan of study (to see course descriptions, please click on the course number under "Degree Requirements"). To find out when courses are offered during a graduate degree in data science, please visit Drexel's Term Master Schedule.
- INFO 623 Social Network Analytics: The goals of this course are to understand the social network analysis methods and how they can be applied in studying the social network properties in both online and physical environments. The course introduces the knowledge and tools necessary for conducting social network analysis which is widely used in the social and behavioral sciences, social computing, economics, marketing, and informatics. The social network perspective focuses on relationship among social entities. It covers graph and matrix representation, centrality and prestige measures, cohesive analysis, positional and role analysis. Students gain practical experience with social network analysis and visualization tools.
- CS 537 Interactive Computer Graphics: This is a project-oriented class that covers the concepts and programming details of interactive computer graphics. These include graphics primitives, display lists, picking, shading, rendering buffers and transformations. Students will learn an industry-standard graphics system by implementing weekly programming assignments. The course culminates with a student-defined project.
- INFO 591 Data and Digital Stewardship: Examines traditional and emerging approaches to data management, data curation, and data service across the full range of information organizations (including, libraries, archives, museums, data centers, software industries, etc.). Introduces foundations of data infrastructures and data representation in all the activities related to care and management of digital objects over their lifecycles. Discusses methods and issues related to accessibility, security, preservation, privacy and ethics of using and managing digital records.
Additional Data Science Graduate Program Courses: Certificate and Minor Options
Post-Baccalaureate Certificates in Applied Data Science and Computational Data Science are also available. Students who complete either certificate prior to enrolling in MSDS may transfer up to 12 credits toward the MSDS degree.
For current graduate students who are interested in bolstering their master's degree with data science concepts, the College offers graduate minors in Applied Data Science and Computational Data Science.