This specialization provides technical and leadership training required for key positions in information technology, data science and analytics. It provides an understanding of how to work in professional roles in today’s data-intensive and data-driven world. It reviews key technologies in analytics and business intelligence drawing from both traditional statistics and machine learning.
Curriculum
Core Courses (4 units)
Specialization Courses (7 units)
Course List
| Course |
Title |
| CIS 435-DL | Practical Data Science Using Machine Learning |
| MSDS 400-DL | Math for Modelers |
| MSDS 401-DL | Applied Statistics with R |
| Supervised Learning Methods |
| Unsupervised Learning Methods |
| Natural Language Processing |
| Data Visualization |
| Artificial Intelligence and Deep Learning |
| Decision Analytics |
About the Final Project
Students may pursue their capstone experience independently or as part of a team. As their final course, students take either the individual research project in an independent study format or the classroom final project class in which students integrate the knowledge they have gained in the core curriculum in a project presented by the instructor. In both cases, students are guided by faculty in exploring the body of knowledge on information systems while contributing research of practical value to the field. The capstone independent project and capstone class project count as one unit of credit.
Course List | Course | Title |
| Computer Information Systems Capstone Project |
| Capstone Research |