Information Systems, MS Artificial Intelligence Specialization

Recent advances in machine learning and artificial intelligence are affecting the work of data scientists and information systems professionals. Traditional artificial intelligence utilized rules-based, knowledge-based systems and logic programming. Today's artificial intelligence relies on machine learning methods and deep learning, in particular. Data science encompasses traditional statistics, operations research, and machine learning methods. Machine learning methods include naïve Bayes models, nearest neighbor models, classification and regression trees, random forests, support vector machines, and neural networks. Machine learning methods are data-adaptive—they learn from data. Advances in artificial intelligence rely on deep learning, which involves neural networks with many hidden layers learning from very large data sets. Artificial intelligence is a special area of study within data science and information systems. It has important applications in computer vision, natural language processing, and robotics.


Core Courses (4 units)

Course Title
CIS 413-DLTelecommunications Networks
MSDS 430-DLPython for Data Analysis
CIS 417-DLDatabase Systems Design & Implementation
CIS 498-DLInformation Systems Project
or CIS 590-DL Capstone Research

Specialization Courses (7 units)

Course Title
CIS 435-DLPractical Data Science Using Machine Learning
MSDS 453-DLNatural Language Processing
MSDS 458-DLArtificial Intelligence and Deep Learning
MSDS 462-DLComputer Vision
MSDS 464-DLIntelligent Systems and Robotics
Any two electives
Web Application Development
Database Administration
Big Data Management and Analytics
Fundamentals of Network Security
Advanced Cyber Security
Disaster Recovery and Continuity
Management of Information Security
Innovation with Blockchain Technology
Information Technology Management
Information Technology Strategy
Project Management Concepts
IT Project Management
Information Technology Business Writing and Communication

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 Title
Choose one
Information Systems Project
Capstone Research