Graduate Certificate in Data Science
The Science Academy, housed in the College of Computer, Mathematical, and Natural Sciences (CMNS), draws on the university’s collective expertise to provide academic programs that are both rigorous and relevant. Science Academy Graduate Programs translate research into applied knowledge and provides current and future professionals with invaluable skills.
Mentoring and advising are an essential part of the program. Students meet with faculty and the academic program director to ensure that educational goals and career learning and development goals are met. Students should contact the contact the program director, Amy Chester via email: firstname.lastname@example.org.
The Graduate Certificate in Data Science, In Person (Z104) has a 12-credit, 4-course curriculum that provides a broad introduction to the field—including how to extract and clean data, store and manage large volumes of data, and analyze such data and extract insights from it.
- Provides an advanced introduction to the field and a strong foundation to develop future expertise.
- Data Science requires the ability to integrate data, operate on data at scale, analyze data, make predictions, find patterns and form and test hypothesis. It incorporates practices from a variety of fields in computer science, chiefly Machine Learning, Statistics, Databases, and Visualization.
- Can be completed in nine months of continuous part-time enrollment. See Designation of Full-time/Part-time Status.
Below is a listing of all program courses. For a detailed course description that includes pre-requisites or co-requisites, see The Graduate School Catalog, Course Listing as follows: DATA Course Descriptions.
|Core||DATA601||Probability and Statistics|
|Core||DATA602||Principles of Data Science|
|Core||DATA604||Data Representation and Modeling|
|Elective||DATA603||Principles of Machine Learning|
|Elective||DATA605||Big Data Systems|
|Elective||DATA606||Algorithms for Data Science|
- See the sample plan of study, below. Students should use this as a guide to develop a plan with the academic program director.
- Actual course offerings are determined by the program and may vary semester to semester. Students should note if a course has a pre-requisite or co-requisite.
- Specific class meeting information (days and time) is posted on UMD’s interactive web service services, Testudo. Once on that site, select “Schedule of Classes,” then the term/year. Courses are listed by academic unit.
- The program uses specific section codes for registration, which are listed on the sample plan of study.
|Semester||Year||Course Number||Section Code||Credits|
- Classes meet in UMD College Park campus classrooms, offering a focused, distraction-free learning environment.
- Classes held weekday evenings (e.g., after 5:00 p.m.) to accommodate the working professional’s schedule.
- Uses the semester academic calendar with classes held in the fall and spring semester (16 weeks each).
- Instruction provided by University of Maryland faculty and professionals in the field.
- Instructors present dynamic and interactive seminar-style instruction.
- Students enrolled in a program that features in-person instruction are required to submit the University’s Immunization Record Form prior to the first day of their first semester/term. See Health Requirements.