Data Science MSDS
Major: Data Science
Degree Awarded: Master of Science in Data Science (MSDS)
Calendar Type: Quarter
Minimum Required Credits: 45.0
Co-op Option: Graduate Co-op
Classification of Instructional Programs (CIP) code: 30.7001
Standard Occupational Classification (SOC) code: 15-1111
About the Program
The Master of Science in Data Science program provides a strong foundation in the emerging area of data science with foci on data management and accountability, visualization and communication, and computational, algorithmic, and applied processing techniques. Students gain competency in fundamental methods and techniques for data collection, management, analysis, and result interpretation. Their fundamental understanding and skills will be applied to real-world data analysis tasks through state-of-the-art technologies, tools, and platforms.
A graduate co-op is available; for more information, visit the Steinbright Career Development Center's website.
Admission Requirements
The Master of Science in Data Science accepts applicants who hold a bachelor's degree from an accredited university. Please visit the College of Computing & Informatics website for more information on admission requirements.
Additional Information
For more information, please visit the College of Computing & Informatics (CCI) website.
Degree Requirements
Required Certificates | ||
Data Science Foundations | ||
DSCI 511 | Data Acquisition and Pre-Processing | 3.0 |
DSCI 521 | Data Analysis and Interpretation | 3.0 |
Choose 2 courses from the following: | 6.0 | |
Programming Foundations | ||
or CS 501 | Introduction to Programming | |
Data Structures and Algorithms | ||
Systems Basics | ||
Introduction to Software Design | ||
Quantitative Foundations of Data Science | ||
Foundations of Data and Information | ||
Database Management Systems | ||
Information Systems Analysis and Design | ||
Information Visualization | ||
Introduction to Data Analytics | ||
Information Policy and Ethics | ||
Machine Learning for Data Science | ||
DSCI 631 | Applied Machine Learning for Data Science | 3.0 |
DSCI 641 | Recommender Systems for Data Science | 3.0 |
Choose 2 of the following: | 6.0 | |
Programming Foundations | ||
or CS 501 | Introduction to Programming | |
Data Structures and Algorithms | ||
Introduction to Computer Vision | ||
Machine Learning | ||
Applications of Machine Learning | ||
Deep Learning | ||
Quantitative Foundations of Data Science | ||
Data Analysis and Interpretation | ||
Natural Language Processing with Deep Learning | ||
Social Network Analytics | ||
Required Core Course | ||
DSCI 632 | Applied Cloud Computing | 3.0 |
Required Capstone Courses | ||
DSCI 591 | Data Science Capstone I | 3.0 |
DSCI 592 | Data Science Capstone II | 3.0 |
Electives or Optional Third Certificate | 12.0 | |
Students can choose any combination of any courses listed below for a total of 45.0 credits (12.0 credits beyond the required 33.0 credits). If a student chooses all courses listed in a single area, they may apply for a graduate certificate in that area. A degree student may receive a maximum of three certificates. | ||
Students can apply for a third (optional) certificate such as Big Data Analytics PBC, HCI/UX Research and Design PBC, and Applied AI/ML PBC. | ||
A course cannot be used to satisfy multiple parts of the degree requirements. | ||
Big Data Analytics (optional 3rd certificate) | ||
Applied Cloud Computing | ||
Social Network Analytics | ||
Choose 2 of the following: | ||
Programming Foundations | ||
or CS 501 | Introduction to Programming | |
Data Structures and Algorithms | ||
High Performance Computing | ||
Deep Learning | ||
Distributed Systems Software | ||
Data Analysis at Scale | ||
Introduction to the Digital Environment | ||
Cloud Technology | ||
Cloud Security and Virtual Environments | ||
Quantitative Foundations of Data Science | ||
Data Analysis and Interpretation | ||
Natural Language Processing with Deep Learning | ||
Database Management Systems | ||
Applied Database Technologies | ||
Applied AI/ML (optional 3rd certificate) | ||
Introduction to Programming | ||
or CS 570 | Programming Foundations | |
Applications of Machine Learning | ||
Applied Artificial Intelligence | ||
Choose 1 of the following: | ||
Data Structures and Algorithms | ||
Systems Basics | ||
Quantitative Foundations of Data Science | ||
Data Acquisition and Pre-Processing | ||
Data Analysis and Interpretation | ||
Applied Machine Learning for Data Science | ||
Knowledge-based Systems | ||
Explainable Artificial Intelligence | ||
Human–Artificial Intelligence Interaction | ||
HCI/UX Research and Design (optional 3rd certificate) | ||
Information Innovation through Design Thinking | ||
or DSRE 620 | Design Problem Solving | |
Designing with Data | ||
Understanding Users: User Experience Research Methods | ||
Prototyping the User Experience | ||
Additional appropriate graduate level (500-899) Data Science (DSCI), Information Systems (INFO), Computer Science (CS), Software Engineering (SE), or Artificial Intelligence, consulting with your advisor. | ||
Optional Coop Experience * | 0-1 | |
Career Management and Professional Development for Master's Degree Students | ||
Total Credits | 45.0-46.0 |
- *
Co-op is an option for this degree for full-time on-campus students. To prepare for the 6-month co-op experience, students will complete COOP 500. The total credits required for this degree with the co-op experience is 46.0
Students not participating in the co-op experience will need 45.0 credits to graduate.
Sample Plan of Study
Part-time, no co-op
First Year | |||||||
---|---|---|---|---|---|---|---|
Fall | Credits | Winter | Credits | Spring | Credits | Summer | Credits |
CS 570 | 3.0 | DSCI 521 | 3.0 | DSCI 631 | 3.0 | Vacation | |
DSCI 511 | 3.0 | DS Foundations Elective | 3.0 | Certificate Course or Elective | 3.0 | ||
6 | 6 | 6 | 0 | ||||
Second Year | |||||||
Fall | Credits | Winter | Credits | Spring | Credits | Summer | Credits |
Machine Learning for DS Elective | 3.0 | DSCI 632 | 3.0 | Machine Learning for DS Elective | 3.0 | Vacation | |
Certificate Course or Elective | 3.0 | DS Foundation Elective | 3.0 | Certificate Course or Elective | 3.0 | ||
6 | 6 | 6 | 0 | ||||
Third Year | |||||||
Fall | Credits | Winter | Credits | ||||
DSCI 591 | 3.0 | DSCI 592 | 3.0 | ||||
Certificate Course or Elective | 3.0 | ||||||
6 | 3 | ||||||
Total Credits 45 |
Note: Third Year Winter is less than the 4.5-credit minimum required (considered half-time status) of graduate programs to be considered financial aid eligible. As a result, aid will not be disbursed to students this term
Full-time with co-op
First Year | |||||||
---|---|---|---|---|---|---|---|
Fall | Credits | Winter | Credits | Spring | Credits | Summer | Credits |
COOP 500 | 1.0 | DSCI 521 | 3.0 | DSCI 631 | 3.0 | DSCI 632 | 3.0 |
CS 570 | 3.0 | DS Foundations Elective | 3.0 | Certificate Courses or Electives | 6.0 | DSCI 591 | 3.0 |
DSCI 511 | 3.0 | Machine Learning for DS Elective | 3.0 | Certificate Course or Elective | 3.0 | ||
DS Foundations Elective | 3.0 | ||||||
10 | 9 | 9 | 9 | ||||
Second Year | |||||||
Fall | Credits | Winter | Credits | Spring | Credits | ||
COOP EXPERIENCE | COOP EXPERIENCE | DSCI 592 | 3.0 | ||||
Machine Learning for DS Elective | 3.0 | ||||||
Certificate Course or Elective | 3.0 | ||||||
0 | 0 | 9 | |||||
Total Credits 46 |
Note: Second Year Summer is less than the 4.5-credit minimum required (considered half-time status) of graduate programs to be considered financial aid eligible. As a result, aid will not be disbursed to students this term.
Facilities
3675 Market Street
The College of Computing & Informatics is located at 3675 Market. Occupying three floors in the modern uCity Square building, CCI's home offers state-of-the-art technology in our classrooms, research labs, offices, meeting areas and collaboration spaces. 3675 Market offers Class A laboratory, office, coworking, and convening spaces. Located at the intersection of Market Street and 37th Street, 3675 Market acts as a physical nexus, bridging academic campuses and medical centers to the east and south, the commercial corridors along Market Street and Chestnut Street, and the residential communities to the north and west.
The uCity Square building offers:
- Speculative lab/office space
- World-class facilities operated by CIC
- Café/restaurant on-site
- Quorum, a two-story, 15K SF convening space and conference center
- Adjacent to future public square
- Access to Science Center’s nationally renowned business acceleration and technology commercialization programs
Drexel University Libraries
The Drexel University Libraries is a one-stop resource for all members of the Drexel community, providing access to millions of print and online books, journals, databases and other media, as well as hundreds of online course and research guides, workshops, and tutorials. Expert librarians offer a variety of consultation services virtually or in person, including help with course-related projects, strategies for finding and evaluating authoritative information, and approaches to utilizing, organizing, and presenting scholarship.
Students in the College of Computing & Informatics also have access to the W. W. Hagerty Library where they can take advantage of the Libraries’ various learning environments, including group study rooms, collaborative and silent study areas, and 24/7 study space in the Dragons’ Learning Den. The Libraries also offers a wellness room, printing and scanning services, and laptops, portable power chargers, and other equipment you can borrow for use in the Library.
CCI Commons
Located on the 10th floor of 3675 Market Street, the CCI Commons is an open lab and collaborative work environment for students. It features desktop computers, a wireless/laptop area, free black and white printing, and more collaborative space for its students. Students have access to 3675 Market's fully equipped conference room with 42” displays and videoconferencing capabilities. The CCI Commons provides technical support to students, faculty, and professional staff. In addition, the staff provides audio-visual support for all presentation classrooms within 3675 Market. Use of the CCI Commons is reserved for all students taking CCI courses.
The computers for general use are Microsoft Windows and Macintosh OSX machines with appropriate applications which include the Microsoft Office suite, various database management systems, modeling tools, and statistical analysis software. Library-related resources may be accessed at the CCI Commons and through the W.W. Hagerty Library. The College is a member of the "Azure Dev Tools for Teaching” platform that allows students free access to a wide array of Microsoft software titles and operating systems.
The CCI Commons, student labs, and classrooms have access to networked databases, print and file resources within the College, and the Internet via the University’s network. Email accounts, Internet and BannerWeb access are available through the Office of Information Resources and Technology.
Computer Support for Teaching
The CCI server room houses a multitude of servers to support faculty research, staff operations, and student learning. Services provided include a Linux compute cluster which is open to all faculty, staff, and students, multiple virtualization environments to meet different needs of faculty, staff, and students, and other single-purpose servers to support various operations throughout the college. The compute cluster provides a common environment for students to develop software, which makes testing easier for the TAs and faculty. Our virtualization environments allow college members the flexibility of a cloud environment with local support and direct cost recovery options. For those who need dedicated hardware, we also support dedicated research systems.
Classrooms are outfitted with laser projectors, 4K displays, class capture hardware, and the Wolfvision Cynap. The Cynap controls the AV distribution throughout the room and can display up to 4 streams simultaneously. These include the local PC, a laptop connected directly to the podium, or up to 4 streaming devices. Windows, macOS, iOS and Android devices can all connect wirelessly to the presentation system, allowing collaboration and freedom to roam the classroom for better interactivity. Wireless networking and outlets are also available for students throughout the classrooms. Laptops are available for checkout from the CCI Commons desk.
Additionally, CCI is hosting and supporting multiple Virtual Computing Lab environments for students to use that mimics the physical computer labs in CCI. This technology allows both online and face to face students to have the same experience when using computing facilities.
CCI Virtual Environments
CCI hosts a variety of virtual environments, which support all levels of research, academics, and administration at CCI. These include OpenStack, Proxmox VE, VMWare, and Xen architectures, backed by storage in CEPH. Multiple environments allow CCI IT to provide researchers with the level of control appropriate for the project at hand and make efficient use of project funding. External cloud vendors such as AWS and Google Cloud Platform are also used when appropriate.
CCI continues to invest in these virtual environments, and explores emerging environments, to continue to best support CCI research and teaching. CPU cores, storage, and memory are added at every opportunity to these flexible, scalable environments. The current capacity of the system includes:
- 1760 CPU Cores
- 6 TB of Memory
- Over 556 TB of HDD-backed storage
- 122 TB of high-performance SSD-backed storage
- 12 GPUs with room for expansion through funded research for high-performance computing needs
CCI Learning Center
The CCI Learning Center (CLC), located in 3675 Market Street's CCI Commons student computer lab, provides consulting and other learning resources for students taking courses offered by the Computer Science Department. The CLC is staffed by graduate and undergraduate computer science students from the College of Computing & Informatics.
The CLC and CCI Commons serve as a central hub for small group work, student meetings, and TA assistance.
Research Laboratories
The College houses multiple research labs, led by CCI faculty, in 3675 Market Street including: the Metadata Research Center (MRC), Interactive Systems for Healthcare (IS4H) Research, Economics and Computation (EconCS), The TeX-Base Lab, SPiking And Recurrent SoftwarE (SPARSE) Coding, Human-System Evaluation and Analysis Lab (H-SEAL), Applied Symbolic Computation Laboratory (ASYM), Security and Privacy Analytics Lab (SePAL), Software Engineering and Analytics Research (SOAR), Software Engineering Research Group (SERG), Social Computing Research Group, Vision and Cognition Laboratory (VisCog). For more information on these laboratories, please visit the College’s research web page.