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 420-DL : Database Systems
Description
This course introduces data management and data preparation with
a focus on applications in large-scale analytics projects utilizing
relational, document, graph, and graph-relational databases.
Students learn about the relational model, the normalization
process, and structured query language. They learn about data
cleaning and integration, and database programming for extract,
transform, and load operations. Students work with unstructured
data, indexing and scoring documents for effective and relevant
responses to user queries. They learn about graph data models and
query processing. Students write programs for data preparation and
extraction using various data sources and file formats.
Recommended: Prior programming experience or MSDS
430-DL Python for Data Science.
Prerequisite: MSDS 402-DL Introduction to Data Science or
MSDS 403-DL Data Science in Practice.
Formerly titled, "Database Systems and Data Preparation."
Starting in fall 2023, this course will have no
prerequisites.
