Courses
Sample Full-Time Schedule
View an example of a full-time course schedule below.
Year 1
Fall Semester
Principles of Learning and Motivation for Design
Understand design and advancement of learning and motivation outcomes in various environments through a systematic examination and application of current research.
Data-Informed Learning Design A
Explore research design, data collection, assessment and evaluation methods.
Introduction to Computational Thinking and Data Science
Introduction to data analysis techniques and associated computing concepts for non-programmers.
Spring Semester
Designing Inclusive and Accessible Instruction
Examine various research designs and their appropriateness for addressing different research questions, threats to validity and other challenges in research, and basic statistical methods and their use.
Principles of Programming for Data Science
Programming in Python for retrieving, searching and analyzing data from the Web. Learning to manipulate large data sets.
Year 2
Fall Semester
AI and Learning Technologies A
Explore current and emerging generative AI and other educational technologies to enhance learning and instructional design.
Data Science at Scale
Big data informatics fundamentals. Data lifecycle; the data scientist; machine learning; data mining; NoSQL databases; tools to store, process, analyze large data sets on clusters.
Spring Semester
AI and Learning Technologies B
Design AI-enhanced, multimedia-rich learning experiences.
Data-Informed Learning Design C
Analyze and present data using visualizations and other formats. Apply data insights to support decision-making
Viterbi Elective
Elective Course