Storing, managing, and processing datasets are foundational processes in data science. This course introduces the fundamental knowledge and skills of data engineering that are required to be effective as a data scientist. This course focuses on the basics of data pipelines, data pipeline flows and associated business use cases, and how organizations derive value from data and data engineering. As these fundamentals of data engineering are introduced, learners will interact with data and data processes at various stages in the pipeline, understand key data engineering tools and platforms, and use and connect critical technologies through which one can construct storage and processing architectures that underpin data science applications.

Requisites

• MIDS students only. Intermediate competency in Python, C, or Java, and competency in Linux, GitHub, and relevant Python libraries. Knowledge of database management including SQL is recommended but not required.

Credit Restrictions

Students will receive no credit for DATASCI W205 after completing DATASCI 205. A deficient grade in DATASCI W205 may be removed by taking DATASCI 205.

Repeat Rules

Course is not repeatable for credit.