Course Requirements
Introductory Courses
Course List | Course | Title | Quarter Hours |
| IT 403 | STATISTICS AND DATA ANALYSIS | 4 |
| CSC 412 | TOOLS AND TECHNIQUES FOR COMPUTATIONAL ANALYSIS | 4 |
| CSC 401 | INTRODUCTION TO PROGRAMMING | 4 |
Foundation Courses
Course List | Course | Title | Quarter Hours |
| DSC 441 | FUNDAMENTALS OF DATA SCIENCE | 4 |
| DSC 450 | DATABASE PROCESSING FOR LARGE-SCALE ANALYTICS | 4 |
| DSC 430 | PYTHON PROGRAMMING | 4 |
| DSC 445 | MACHINE LEARNING I | 4 |
| CSC 483 | APPLIED DEEP LEARNING | 4 |
| DSC 465 | DATA VISUALIZATION | 4 |
| CSC 484 | ETHICS IN ARTIFICIAL INTELLIGENCE | 4 |
Advanced Courses
Course List | Course | Title | Quarter Hours |
| DSC 478 | PROGRAMMING MACHINE LEARNING APPLICATIONS | 4 |
| CSC 555 | MINING BIG DATA | 4 |
| 4 |
| ADVANCED MODELING AND ANALYSIS TECHNIQUES | |
| INTRODUCTION TO IMAGE PROCESSING | |
| MONTE CARLO ALGORITHMS | |
| INTELLIGENT INFORMATION RETRIEVAL | |
Elective Courses
Students must select four (4) credit hours of graduate-level elective courses. Students must choose electives from the following list of courses:
Course List | Course | Title | Quarter Hours |
| 4 |
| ADVANCED MODELING AND ANALYSIS TECHNIQUES | |
| TIME SERIES ANALYSIS AND FORECASTING | |
| PROGRAMMING INTERACTIVE DATA VISUALIZATION FOR THE WEB | |
| MONTE CARLO ALGORITHMS | |
| TOPICS IN COMPUTER SCIENCE | |
| PROBABILITY AND STATISTICS I | |
| GENERALIZED LINEAR MODELS | |
| BAYESIAN STATISTICS | |
| ADVANCED BIOSTATISTICS | |
| SURVIVAL ANALYSIS | |
| OPERATIONS RESEARCH: OPTIMIZATION THEORY | |
| INTRODUCTION TO IMAGE PROCESSING | |
| APPLIED IMAGE ANALYSIS | |
| COMPUTER VISION | |
| SPATIAL DATABASES & GEOGRAPHIC INFORMATION SYSTEMS | |
| GEOGRAPHIC INFORMATION SYSTEMS (GIS) FOR COMMUNITY DEVELOPMENT | |
| GEOGRAPHICAL INFORMATION SYSTEMS (GIS) FOR SUSTAINABLE URBAN DEVELOPMENT | |
| INFORMATION VISUALIZATION AND INFOGRAPHICS | |
| |
| RECOMMENDER SYSTEMS | |
| ADVANCED DEEP LEARNING | |
| ARTIFICIAL INTELLIGENCE II | |
| NATURAL LANGUAGE PROCESSING | |
| TOPICS IN ARTIFICIAL INTELLIGENCE | |
| PROGRAMMING MACHINE LEARNING APPLICATIONS | |
| MACHINE LEARNING II | |
| MACHINE LEARNING ENGINEERING FOR PRODUCTION (MLOPS) | |
| DATABASE PROGRAMMING | |
| INTELLIGENT INFORMATION RETRIEVAL | |
| WEB DATA MINING | |
| DATA WAREHOUSING | |
| ENTERPRISE DATA MANAGEMENT | |
| COMPUTATIONAL ADVERTISING | |
| HEALTH DATA SCIENCE | |
| TOPICS IN DATA ANALYSIS | |
| SOCIAL NETWORK ANALYSIS | |
| INFORMATION TECHNOLOGY CONSULTING | |
| BUSINESS INTELLIGENCE AND ANALYTICS SYSTEMS | |
| SPECIAL TOPICS (Managerial & Marketing Epidemiology) | |
| ANALYTICAL TOOLS FOR MARKETERS | |
| MARKETING MANAGEMENT | |
| DIGITAL BUSINESS STRATEGY | |
| DIGITAL MARKETING ANALYTICS & PLANNING | |
| SPECIAL TOPICS (Health Care Data Analysis) | |
| HEALTH SECTOR MANAGEMENT | |
| 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 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:
- Secure an internship with focus in analytics.
- 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)
- 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.