What will you learn in HarvardX: Data Science: Wrangling course
-
Understand the importance of data wrangling in real-world data science workflows.
-
Learn how to clean, transform, and reshape messy datasets into analysis-ready formats.
-
Work with common data issues such as missing values, duplicates, and inconsistent formats.
-
Manipulate datasets using filtering, grouping, joining, and reshaping techniques.
-
Prepare data efficiently for exploratory analysis, visualization, and modeling.
-
Build strong foundations for professional data analysis and data science projects.
Program Overview
Introduction to Data Wrangling
⏳ 1–2 weeks
-
Learn what data wrangling is and why it consumes most of a data scientist’s time.
-
Understand tidy data principles and structured data formats.
-
Explore common real-world data quality challenges.
Data Cleaning and Transformation
⏳ 2–3 weeks
-
Handle missing data, outliers, and inconsistent values.
-
Clean and standardize variables for reliable analysis.
-
Apply transformation techniques to make data usable and meaningful.
Data Manipulation and Reshaping
⏳ 2–3 weeks
-
Filter, sort, and summarize datasets efficiently.
-
Learn grouping and aggregation techniques.
-
Reshape data between wide and long formats for analysis and visualization.
Working with Multiple Data Sources
⏳ 2–3 weeks
-
Combine datasets using joins and merges.
-
Understand relational data concepts in practice.
-
Prepare complex datasets for downstream analytics tasks.
Get certificate
Job Outlook
-
Essential skill set for Data Analysts, Data Scientists, and Researchers.
-
Data wrangling expertise is critical across industries such as finance, healthcare, marketing, and tech.
-
Strong preparation for advanced courses in data visualization, machine learning, and statistical modeling.
-
Improves efficiency, accuracy, and reliability in data-driven roles.
