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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 441FUNDAMENTALS OF DATA SCIENCE4
DSC 450DATABASE PROCESSING FOR LARGE-SCALE ANALYTICS4
DSC 430PYTHON PROGRAMMING4
DSC 445MACHINE LEARNING I4
CSC 483APPLIED DEEP LEARNING4
DSC 465DATA VISUALIZATION4
CSC 484ETHICS IN ARTIFICIAL INTELLIGENCE4

Advanced Courses1

Course Title Quarter Hours
DSC 424ADVANCED MODELING AND ANALYSIS TECHNIQUES4
MKT 555MARKETING MANAGEMENT4
MKT 534ANALYTICAL TOOLS FOR MARKETERS4
1

Some advanced courses may not be offered online. Students may consult with their faculty advisor to determine suitable course substitutions.

Elective Courses

Students must take four (4) credit hours of graduate-level elective courses. Elective courses must be selected from the following list:

Course Title Quarter Hours
Select four (4) credit hours from the following:4
Advanced Data Analysis and Algorithms
DSC 425
TIME SERIES ANALYSIS AND FORECASTING
CSC 468
PROGRAMMING INTERACTIVE DATA VISUALIZATION FOR THE WEB
CSC 521
MONTE CARLO ALGORITHMS
CSC 595
TOPICS IN COMPUTER SCIENCE
MAT 451
PROBABILITY AND STATISTICS I
MAT 426
GENERALIZED LINEAR MODELS
MAT 427
BAYESIAN STATISTICS
MAT 424
ADVANCED BIOSTATISTICS
MAT 425
SURVIVAL ANALYSIS
MAT 488
OPERATIONS RESEARCH: OPTIMIZATION THEORY
Visualization and Image Analysis
CSC 481
INTRODUCTION TO IMAGE PROCESSING
CSC 482
APPLIED IMAGE ANALYSIS
CSC 528
COMPUTER VISION
CSC 543
SPATIAL DATABASES & GEOGRAPHIC INFORMATION SYSTEMS
GEO 441
GEOGRAPHIC INFORMATION SYSTEMS (GIS) FOR COMMUNITY DEVELOPMENT
GEO 442
GEOGRAPHICAL INFORMATION SYSTEMS (GIS) FOR SUSTAINABLE URBAN DEVELOPMENT
HCI 512
INFORMATION VISUALIZATION AND INFOGRAPHICS
Machine Learning and AI
CSC 577
RECOMMENDER SYSTEMS
CSC 578
ADVANCED DEEP LEARNING
CSC 580
ARTIFICIAL INTELLIGENCE II
CSC 583
NATURAL LANGUAGE PROCESSING
CSC 594
TOPICS IN ARTIFICIAL INTELLIGENCE
DSC 478
PROGRAMMING MACHINE LEARNING APPLICATIONS
DSC 545
MACHINE LEARNING II
SE 489
MACHINE LEARNING ENGINEERING FOR PRODUCTION (MLOPS)
Databases and Data Management
CSC 452
DATABASE PROGRAMMING
CSC 555
MINING BIG DATA
CSC 575
INTELLIGENT INFORMATION RETRIEVAL
DSC 484
WEB DATA MINING
IS 549
DATA WAREHOUSING
IS 550
ENTERPRISE DATA MANAGEMENT
Applications
CSC 576
COMPUTATIONAL ADVERTISING
DSC 510
HEALTH DATA SCIENCE
CSC 598
TOPICS IN DATA ANALYSIS
DSC 480
SOCIAL NETWORK ANALYSIS
IS 478
INFORMATION TECHNOLOGY CONSULTING
IS 574
BUSINESS INTELLIGENCE AND ANALYTICS SYSTEMS
MGT 798
SPECIAL TOPICS
MKT 595
DIGITAL MARKETING ANALYTICS & PLANNING
MKT 560
DIGITAL BUSINESS STRATEGY
MGT 559
HEALTH SECTOR MANAGEMENT
MKT 798
SPECIAL TOPICS
CMNS 549
SPECIAL TOPICS IN ORGANIZATIONAL COMMUNICATION

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 695course.
  • 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.