Data Cleaning, Transformation, and Manipulation

In Data Cleaning, Transformation, and Manipulation, you’ll learn to turn messy data into analysis- and modeling-ready datasets using Python (pandas) and SQL. This is a skill-based path organized around real workplace tasks. Each module mirrors responsibilities you see in job descriptions and focuses on the exact steps you’ll perform on the job. You’ll begin with a quick skills check, then personalize your journey: double down on new topics, or skip what you already know. For each skill, you’ll review concise lessons curated from expert instructors with explanations and demos for filtering and subsetting, joins and merges, feature engineering, normalization, encoding, imputation, scaling, and feature selection. Then you will prove your skills in job-task assessments. By the end, you can assemble analysis-ready tables, engineer clean numeric features, and prepare a modeling-ready feature set for predictive modeling. These capabilities support roles like Data Analyst, Analytics Engineer, Business Intelligence Analyst, Data Scientist, or Machine Learning Engineer and help you handle everyday tasks such as combining datasets, cleaning and transforming columns, and delivering ready-to-train features.