Introductory Courses
No Introductory course (a course numbered 400 through 419) may be substituted for any other course at any level.
Introductory courses may be waived for any of the following conditions:
- The student has the appropriate course work to satisfy an Introductory Course.
- The student has appropriate and verified professional experience to satisfy an Introductory Course.
- The student passes a
Graduate Assessment Examination (GAE) in the Introductory Course area.
Foundation Courses
DSC 430 |
DSC 450 |
DSC 423 |
DSC 424 |
DSC 441 |
Students must take
1 course in applied analytics chosen among:
Advanced Courses
Students must take
1 course among the following:
MKT 529 |
MKT 595 |
MKT 798 Topic: Health Care Data Analysis |
MKT 570 |
Note MKT 798 must be approved by program coordinator.
Elective Courses
Students must take
8 credit hours from graduate level elective courses in the areas of statistical modeling, data mining or database technologies according to the following rules:
Students must take
8 credit hours from courses among the following:
DSC 425 |
DSC 430 |
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 |
CSC 555 |
CSC 575 |
CSC 576 |
CSC 578 |
CSC 594 |
CSC 598 |
DSC 484 |
GEO 441 |
GEO 442 |
GPH 565 |
HCI 512 |
IPD 451 |
CMNS 549 |
IS 549 |
IS 550 |
IS 574 |
IS 578 |
Capstone Options
Students have the option of completing a real world Data Analytics Project, or completing the Predictive Analytics capstone course, or participating in an Analytics Internship or completing a Master's Thesis to fulfill their Capstone requirement.
- Data Analytics Project
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 (http://dampa.cdm.depaul.edu). 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 Master's Research 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 Master's Research course. |
- Data Science Capstone course
DSC 672 (Formerly CSC 672) 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. |
- Analytics Internship
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 Graduate Internship 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 “MyInternships” link on the left to start the course enrollment process. |
- Master's Thesis
A student who has made an original contribution to the area (typically, through work done by
CSC 695 Master's Research ) may choose to complete a Master's Thesis. The student and the student's research advisor should form a Master's Thesis Committee of 3 faculty. The student will need to submit to the committee a thesis detailing the results of the research project. After a public defense, the committee will decide whether to accept the thesis. In that case, the student will be allowed to register for the 0 credit course
CSC 698 Master's Thesis and the transcript will show the thesis title as the course topic. |