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Data analytics is one of the most in-demand career paths in todays marketplace for high-skill/high pay jobs.
Organizations across industries collect large amounts of data for a variety of reasons: to gain a competitive advantage, to improve the efficiency of operations, to reduce fraud/waste/abuse, to better understand customers better, among others.
Our program is designed to train students to acquire analytical skills and learn critical methodologies to manage and utilize large amounts of data.
Students with a variety of professional and academic backgrounds can apply to our Data Analytics graduate program. Prerequisite courses are available during the summer for students with a non-tech background.
Our 33-credit program is structured to fit one full academic year, including a sponsored capstone paid internship during summer.
As a graduate in our program in Data Analytics you will develop skill sets in these core areas:
The 33 credits of the MS degree program consist of five three-credit core graduate courses, four three-credit graduate elective courses, and a six-credit capstone course based on a sponsored project work. The core courses are:
- IA 510 - Database Modeling, Design and Implementation
- IA 520 - Optimization Methods for Analytics
- IA 530 - Probability and Statistics for Analytics
- IA 640 - Information Visualization
- IA 650 - Data Mining
Some of the core courses may be waived if the students can demonstrate that their previous undergraduate or graduate coursework contains equivalent material. In those cases, students will be required to take a greater number of elective courses to satisfy 33-credit program requirement.
Elective courses are offered in a variety of areas and they include but are not limited to the following:
- IA 605 - Data Warehousing
- IA 505 Tabular Data Analytics
- IA 630 - Modeling for Insight (pre-requisite: Tabular Data Analytics)
- IA 670 - Geospatial Systems
- CS 549 - Computational/Machine Learning
- CS 551 - Artificial Intelligence
- CS 559 - Human Computer Interaction
- EC 611- Econometrics
- EE 501 - Digital Signal processing
- ES 505 - Design of Experiments and Analysis of Data
- EE 574 - Pattern Recognition
- ME 529, Stochastic Processes for Engineers
- OM 680 - Strategic Project Management
- EC 611 - Econometrics
- MK 696 Marketing Research Methods
IA690 - Capstone Project is a course centered on a sponsored data analytics projects with interdisciplinary teams. Capstone projects, depending on project parameters could consist of a 2 unit seminar w/4 unit project (consistent with engineering curriculum as currently offered) and/or be a mentored capstone of 6 total units. Depending on the nature of the capstone and its sponsorship, projects could be on-site fieldwork intensive.