MS-In-Predictive-Analytics-Marketing

Master of Science 2014-2015

Predictive Analytics

Marketing Concentration
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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.
    *53 graduate credit hours required for MS Information Systems.

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.


Course Requirements
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.
IT 403 Statistics and Data Analysis
CSC 412 Tools and Techniques for Computational Analysis
CSC 401 Introduction to Programming
Foundation Courses
CSC 455 Database Processing for Large-Scale Analytics
CSC 423 Data Analysis and Regression
CSC 424 Advanced Data Analysis
IS 567 Knowledge Discovery Technologies

Students must take 1 course in applied analytics chosen among:
CSC 465 Data Visualization
CSC 495 Social Network Analysis
ECT 584 Web Data Mining for Business Intelligence
CSC 575 Intelligent Information Retrieval
Advanced Courses
MKT 555 Decisions in Marketing Management
MKT 530 Customer Relationship Management
MKT 534 Analytical Tools for Marketers
Students must take 1 course among the following:
MKT 529 Precision Marketing
MKT 595 Internet and Interactive Marketing
MKT 798 Special Topics
Note MKT 798 must be approved by program coordinator.
Elective Courses
Students must take 3 graduate level elective courses in the areas of statistical modeling, data mining or database technologies according to the following rules:

Students must take 1 500-level CDM elective. ANI, DC, TV, and VFX courses do not qualify.

Students must take 2 courses among the following:
CSC 425 Time Series Analysis and Forecasting
CSC 433 Scripting for Data Analysis
CSC 452 Database Programming
CSC 465 Data Visualization
CSC 478 Programming Data Mining Applications
CSC 481 Introduction to Image Processing
CSC 482 Applied Image Analysis
CSC 495 Social Network Analysis
CSC 521 Monte Carlo Algorithms
CSC 529 Advanced Data Mining
CSC 543 Spatial Databases and Geographic Information Systems
CSC 555 Mining Big Data
CSC 575 Intelligent Information Retrieval
CSC 594 Topics in Artificial Intelligence
CSC 598 Topics in Data Analysis
ECT 584 Web Data Mining for Business Intelligence
GEO 441 Geographic Information Systems (Gis) for Community Development
GPH 565 Designing for Visualization
HCI 512 Information Visualization and Infographics
IPD 451 Big Data and NoSQL Program
IS 549 Data Warehousing and Data Mining
IS 574 Business Intelligence
IS 578 Information Technology Consulting
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.
  • Predictive Analytics Capstone course
    CSC 672 Data Analysis Workshop 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. (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 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.