** Admissions to the online program will not be granted to international students residing outside of the U.S.
Students must complete 28 required credit hours and 8 elective credit hours to earn the Data Analytics degree while maintaining a minimum GPA of 3.0 on a scale of 4.0 as listed below.
|CSC 225||Computer Programming Concepts I||3|
|CSC 275||Computer Programming Concepts II||3|
|CSC 302||Discrete Structures||4|
|CSC 385||Data Structures and Algorithms||4|
|DAT 332||Matrix Analysis and Numerical Optimization||4|
|or MAT 332||Linear Algebra|
|MAT 115||Calculus I||4|
|or MAT 113||Business Calculus|
|MAT 121||Applied Statistics||3|
|CSC 472||Introduction to Database Systems||4|
|CSC 532||Introduction to Machine Learning||4|
|CSC 534||Big Data Analytics||4|
|CSC 535||Deep Learning||4|
|DAT 502||Introduction to Statistical Computation||4|
|DAT 530||Advanced Statistical Methods||4|
|DAT 554||Data Analytics Capstone 1||4|
|CSC 533||Data Mining||4|
|CSC 561||NoSQL Databases||4|
|CSC 562||Data Visualization||4|
|CSC 570||Advanced Topics in Computer Systems (Containerization/BigData or A.I. for Cybersecurity)||4|
|CSC 572||Advanced Database Concepts||4|
|DAT 444||Operations Research Methods||4|
|or MAT 444||Operations Research Methods|
The capstone project will draw upon the knowledge and skills learned throughout the entire curriculum and will ask students to apply the appropriate methods and tools for data analysis in a real-world organizational setting. The capstone course provides the opportunity to exercise different techniques for data storage, preprocessing, integration and analysis covered throughout the M.S. in Data Analytics curriculum in order to address business challenges. The students must provide a well-written report and an oral presentation to effectively communicate their findings.
On acceptance, students are assigned their academic advisor. Before registering for the first time, the student should discuss an appropriate course of study with the academic advisor.
Students must earn a grade of B- or better in all courses that apply toward the degree, and a cumulative 3.0 grade point average is required to graduate. In addition, graduate students who do not maintain a 3.0 grade point average will be placed on academic probation according to campus policy. Graduate students enrolled in 400-level courses should expect more stringent grading standards and/or additional assignments. Courses taken on a CR/NC basis will not count toward the degree.
NOTE: Students also should refer to the campus policy on Grades Acceptable Toward Master’s Degrees section of this catalog.
Students are allowed to transfer a maximum of eight graduate semester hours with a grade of B or better. They will be evaluated on a case-by-case basis and approved by a Student Petition. Transfer students will be required to take a minimum of 28 credit hours of Data Analytics core and elective course work at UIS.