Master’s in Data Science for MIT MicroMaster's Graduates
Course Descriptions and Schedule
Please note that course schedules may be amended due to low enrollment, faculty availability, and/or other factors.
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.
