About the course
Cleaning and formatting data, also known as “data wrangling,” are the most under appreciated yet time-consuming steps in the data science pipeline. In real world analyses, data wrangling can consume up to 80% of project time. During this course, students will learn and apply the Extract/ Transform/ Load (ETL) process used by professional data scientists to clean and prep data sets for analysis.
Upon successful completion of the course, students will:
- Understand the time commitment needed for data wrangling
- Identify data sets that may be time-intensive to clean
- Efficiently clean data sets of both structured and unstructured data to prepare for analysis
- Apply the Extract/ Transform/ Load (ETL) process to a data set
- Better estimate the time required for data wrangling tasks
Lawrence Gray is an experienced Data Scientist and Computational Biologist. He is an adjunct faculty member in Georgetown Universitys Data Science Certificate Program, where he teaches Python Basics along with Data Ingestion and Wrangling. Dr. Gray earned his doctorate from the Johns Hopkins Uni...
Because of COVID-19, many providers are cancelling or postponing in-person programs or providing online participation options.
We are happy to help you find a suitable online alternative.