MS Data Science | Computational

Master of Science 2022 through2023

Data Science

About the Program

Computational Methods Concentration

Course Legend

Curriculum Requirements

Introductory Courses

No Introductory Course may be substituted for any other course at any level.

Introductory courses may be waived for any of the following conditions based on faculty review:

  • The student has the appropriate course work to satisfy an Introductory Course based on an official transcript review by faculty and successful grades, typically B or better.
  • The student has appropriate and verified professional experience to satisfy an Introductory Course which is demonstrated through successful completion of a GAE exam.
  • If a Graduate Assessment Examination (GAE) is available for the Introductory Courses, upon successfully completion of a GAE, a waiver will be issued.
IT 403
CSC 412
CSC 401

Foundation Courses

DSC 450
DSC 423
DSC 424
DSC 430
DSC 441

Students must take 1 course in applied analytics chosen among:

DSC 465
DSC 480

Advanced Courses

DSC 478
CSC 555
DSC 540

Students must take 1 course among the following:

CSC 521
CSC 575
CSC 578

Elective Courses

Students must take 8 credit hours from graduate level elective courses in the areas of statistical modeling, data mining or database technologies. Students must choose electives from the following list of courses:

DSC 425
DSC 433
CSC 452
DSC 465
DSC 478
CSC 481
CSC 482
DSC 480
DSC 484
CSC 521
CSC 528
DSC 510
DSC 540
CSC 543
CMNS 549
CSC 555
CSC 575
CSC 576
CSC 577
CSC 578
CSC 594
CSC 598
GEO 441
GEO 442
GPH 565
HCI 512
IPD 451
IS 549
IS 550
IS 574
IS 478
MGT 559
MGT 798 Topic: Managerial & Marketing Epidemiology*
MKT 555
MKT 530
MKT 534
MKT 595
MKT 570 Topic: Service Design & Patient Experience*
MKT 798 Topic: Health Care Data Analysis

*Course is not currently offered online.

NOTE: Student must take only sections of MGT 798 and MKT 798 with the topic specified above.

Capstone Options

Students have the option of completing a real world Data Analytics Project, or completing the Data Science capstone course, or participating in an Analytics Internship or completing a Master's Thesis to fulfill their Capstone requirement.

The real data analytics project is for students who are interested in working in a small team on a research project under the supervision of a CDM faculty. A list of available projects is published on the dampa center website ( Student who are interested in proposing their own data analytics project are encouraged to contact a CDM faculty member teaching analytics courses as soon as possible. Students must enroll in CSC 695 for a total of 4 credit hours taken in two consecutive quarters (2 credit hours for 2 quarters) to satisfy the capstone requirement. The faculty who supervises the project will initiate enrollment in the CSC 695 course.

DSC 672 (formerly CSC672) course offers the opportunity of working on an analytics project in a more structured class format. Students enrolled in the courses will be working in teams on a data analytics project under the supervision of the course instructor.

An internship offers students the opportunity to integrate their academic experience with on-the-job training in an analytics related field. Students must enroll in CSC 697 for 4 credit hours to satisfy the capstone requirement. These are the steps: 1) Secure an internship with focus in analytics. 2) International Students must obtain the appropriate practical training form and meet with an advisor in the CDM Academic Center for approval. ISS Forms 3) Login to MyCDM and click the “Internships” link on the left to start the course enrollment process.

A student who is working on a research project and has made an original contribution to their area of study may choose to complete a Master's Thesis. Additional information and requirements for School of Computing students pursuing the thesis option can be found on the SoC Master's Thesis Guideline page.

Degree Requirements

Students in this degree program must meet the following requirements:

  • Complete a minimum of 52 graduate credit hours in addition to any required introductory courses of the designated degree program.
  • Complete all graduate courses and requirements listed in the designated degree program.
  • Earn a grade of C- or better in all courses of the designated program.
  • Maintain a cumulative GPA of 2.5 or higher.
  • Students pursuing a second (or more) graduate degree may not double count or retake any course that applied toward the completion of a prior graduate degree. If a required course in the second degree was already completed and applied toward a previous degree, the student must meet with a faculty advisor to discuss a new course to be completed and substituted in the new degree. This rule also applies to cross-listed courses, which are considered to be the same course but offered under different subjects.
  • Students pursuing a second master's degree must complete a minimum of 52 graduate credit hours beyond their first designated degree program in addition to any required introductory courses in their second designated degree program.

Students with a GPA of 3.9 or higher will graduate with distinction.

For DePaul's policy on repeat graduate courses and a complete list of academic policies see the DePaul Graduate Handbook in the Course Catalog.