Course Schedule, Part-time Online Program

Please note that course schedules may be amended due to low enrollment, faculty availability, and/or other factors.

Online Sync Sessions are an integral part of the online learning experience. Additional information about learning concepts and assignments may be discussed and sync sessions offer valuable opportunities for students to interact with their faculty and peers during the term. We encourage all students to attend live, but if they are unable to, sync sessions will be recorded and posted within Canvas to allow for an asynchronous model of success as well.

MSDS 436-DL : Analytics Systems Engineering


Description

This course introduces design principles and best practices for implementing large-scale systems for data ingestion, processing, storage, and analytics. Students learn about cloud-based computer architecture and scalable systems for data science. They evaluate performance and resource utilization in batch, interactive, and streaming environments. Students review protocols for application programming interfaces. They compare data models, resource requirements, and performance of applications implemented with relational versus graph database systems.

Recommended prior course: MSDS 432-DL Foundations of Data Engineering.

Prerequisites: (1) MSDS 420-DL Database Systems and Data Preparation or CIS 417 Database Systems Design and Implementation and (2) MSDS 422-DL Practical Machine Learning or CIS 435 Practical Data Science Using Machine Learning.


Fall 2022
Start/End DatesDay(s)TimeBuildingSection
09/20/22 - 12/10/22Sync Session Th
7 – 9:30 p.m. 55
InstructorCourse LocationStatusCAESAR Course ID
Bharadwaj, Shreenidhi
Online
Open

Spring 2023
Start/End DatesDay(s)TimeBuildingSection
03/27/23 - 06/10/23Sync Session Th
7 – 9:30 p.m. 55
InstructorCourse LocationStatusCAESAR Course ID
Bharadwaj, Shreenidhi
Online
Open
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