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
Enrollment in this course is restricted. Students must submit an application and be accepted into the Certificate in Data Science in order to register for this course.
Current Georgetown students must create an application using their Georgetown NetID and password. New students will be prompted to create an account.
Course prerequisites include:
- A bachelor's degree or equivalent
- Completion of at least two college-level math courses (e.g. statistics, calculus, etc.)
- Successful completion of Data Sources (XBUS-502)
- Basic familiarity with programming or a programming language
- A laptop for class meetings and coursework