Course Description
Focuses on cloud computing, platform technologies, and integration of distributed data sources. New technologies like reinforcement learning are introduced in this course. Project work will be focused on innovation topics provided by companies from FinTech, agriculture, manufacturing, and others.
Additional Requirements for Graduate Students:
Graduate students will also work on and complete an additional research task pertaining to applications and innovations in the industry. Graduate students must provide a survey of the literature and papers published in the context of the research task. A research report to document findings will be used as an additional assessment.
Athena Title
Informatics III
Equivalent Courses
Not open to students with credit in INFO 4000E or INFO 6000E
Prerequisite
INFO 3000 or INFO 3000E
Semester Course Offered
Offered every year.
Grading System
A - F (Traditional)
Course Objectives
Upon successful completion of this course, students will be able to: • Understand and use cloud computing and parallel computing techniques. • Do advanced data integration from distributed data sources. • Understand and apply Reinforcement learning concepts and techniques and their applications in the industry. • Understand platform technologies and their applications. • Do advanced hands-on project work on company-sponsored projects in various industry verticals.
Topical Outline
Data Management Systems: Data Sources - Data Lakes, ERP Systems, Banking Systems Data Integration - Of Different Sources and Types of Data Reinforcement Learning: Reinforcement Learning - Concepts and Applications Advanced Computing: Cloud Computing and Parallel Computing - AWS, GPUs, Map-Reduce Platform Technologies - FinTech Platforms Clinical Work and Innovation: Sandbox Projects – Innovation in Industry Applications Programming - API Based Data Integration with Industry Data Sources
Syllabus