Course Descriptions and Schedule

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

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 learn how to package and distribute containerized computer software. They apply tools of systems analysis, evaluating end-to-end performance and resource utilization in batch, interactive, and streaming environments. Students review formats and protocols for application programming interfaces. They compare data models, resource requirements, and performance of applications implemented with relational versus graph database systems.

Prerequisites: (1) MSDS 432-DL Foundations of Data Engineering and (2) MSDS 422-DL Practical Machine Learning or CIS 435 Practical Data Science Using Machine Learning.


Spring 2021
Start/End DatesDay(s)TimeBuildingSection
03/29/21 - 06/06/21Optional Sync W
7 – 9:30 p.m. 55
InstructorCourse LocationStatusCAESAR Course ID
Bharadwaj, Shreenidhi
Online
Open
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