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Course Requirements

Introductory Courses

Course Title Quarter Hours
IT 403STATISTICS AND DATA ANALYSIS4
CSC 412TOOLS AND TECHNIQUES FOR COMPUTATIONAL ANALYSIS4
CSC 401INTRODUCTION TO PROGRAMMING4

Foundation Courses

Course Title Quarter Hours
DSC 450DATABASE PROCESSING FOR LARGE-SCALE ANALYTICS4
DSC 423DATA ANALYSIS AND REGRESSION4
DSC 430PYTHON PROGRAMMING4
DSC 441FUNDAMENTALS OF DATA SCIENCE4
Select one of the following applied analytics courses:4
DSC 424
ADVANCED DATA ANALYSIS
DSC 465
DATA VISUALIZATION

Advanced Courses

Course Title Quarter Hours
DSC 478PROGRAMMING MACHINE LEARNING APPLICATIONS4
CSC 555MINING BIG DATA4
DSC 540ADVANCED MACHINE LEARNING4
Select one of the following: 4
CSC 521
MONTE CARLO ALGORITHMS
CSC 575
INTELLIGENT INFORMATION RETRIEVAL
CSC 578
NEURAL NETWORKS AND DEEP LEARNING

Elective Courses

Students must select eight (8) Credit Hours of 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:

Course Title Quarter Hours
Select eight (8) credit hours from the following:8
CMNS 549
SPECIAL TOPICS IN ORGANIZATIONAL COMMUNICATION
CSC 452
DATABASE PROGRAMMING
CSC 468
PROGRAMMING INTERACTIVE DATA VISUALIZATION FOR THE WEB
CSC 481
INTRODUCTION TO IMAGE PROCESSING
CSC 482
APPLIED IMAGE ANALYSIS
CSC 484
ETHICS IN ARTIFICIAL INTELLIGENCE
CSC 521
MONTE CARLO ALGORITHMS
CSC 528
COMPUTER VISION
CSC 543
SPATIAL DATABASES & GEOGRAPHIC INFORMATION SYSTEMS
CSC 555
MINING BIG DATA
CSC 575
INTELLIGENT INFORMATION RETRIEVAL
CSC 576
COMPUTATIONAL ADVERTISING
CSC 577
RECOMMENDER SYSTEMS
CSC 578
NEURAL NETWORKS AND DEEP LEARNING
CSC 580
ARTIFICIAL INTELLIGENCE II
CSC 583
NATURAL LANGUAGE PROCESSING
CSC 594
TOPICS IN ARTIFICIAL INTELLIGENCE
CSC 598
TOPICS IN DATA ANALYSIS
DSC 425
TIME SERIES ANALYSIS AND FORECASTING
DSC 433
SCRIPTING FOR DATA ANALYSIS
DSC 465
DATA VISUALIZATION
DSC 478
PROGRAMMING MACHINE LEARNING APPLICATIONS
DSC 480
SOCIAL NETWORK ANALYSIS
DSC 484
WEB DATA MINING
DSC 510
HEALTH DATA SCIENCE
DSC 540
ADVANCED MACHINE LEARNING
GEO 441
GEOGRAPHIC INFORMATION SYSTEMS (GIS) FOR COMMUNITY DEVELOPMENT
GEO 442
GEOGRAPHICAL INFORMATION SYSTEMS (GIS) FOR SUSTAINABLE URBAN DEVELOPMENT
GPH 565
DESIGNING FOR VISUALIZATION
HCI 512
INFORMATION VISUALIZATION AND INFOGRAPHICS
IPD 451
BIG DATA AND NOSQL PROGRAM
IS 478
INFORMATION TECHNOLOGY CONSULTING
IS 549
DATA WAREHOUSING
IS 550
ENTERPRISE DATA MANAGEMENT
IS 574
BUSINESS INTELLIGENCE AND ANALYTICS SYSTEMS
MGT 559
HEALTH SECTOR MANAGEMENT
MGT 798
SPECIAL TOPICS (Managerial & Marketing Epidemiology)
MKT 555
MARKETING MANAGEMENT
MKT 530
CUSTOMER RELATIONSHIP MANAGEMENT
MKT 534
ANALYTICAL TOOLS FOR MARKETERS
MKT 595
DIGITAL MARKETING ANALYTICS & PLANNING
MKT 798
SPECIAL TOPICS (Health Care Data Analysis)

Capstone Options

Four (4) credit hours are required for the capstone requirement. Students have the option of completing a real world Data Analytics Project, or completing the Data Science Capstone course, or participating in a Data 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). Students 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.
  • Predictive Analytics Capstone course
    • DSC 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 for 4 credit hours to satisfy the practicum 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. (http://oiss.depaul.edu/Requests/Forms/index.asp)
      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 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 hour course CSC 698 and the transcript will show the thesis title as the course topic.