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. A 2017 study by IBM shows that the annual demand for data scientists, data developers and data engineers will reach nearly 700,000 openings by 2020.
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 Master Program Features
- Dynamic, interdisciplinary program taught by world class faculty from CCI's information science and computer science departments
- A graduate degree 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 no prior background 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).
Apply to the program.
Customize your degree with electives.
Gain real world experience.
Complete Your Data Science Masters Degree:
- On Campus
Master of Computer Science in 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.
Data Science 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.