Data Wrangling, Analysis, and Visualization for Beginners

Raw data is rarely ready for analysis, often filled with missing values, duplicates, and formatting errors. To make reliable data-driven decisions, you must first know how to clean, structure, and interpret this information. This text-only course guides you through the essential stages of the data pipeline, transforming raw, chaotic files into polished, actionable insights. You will build a strong foundation in modern data preparation techniques and learn how to present your findings clearly. What you'll learn: 1. Understand foundational data types, structures, and tidy data principles. 2. Clean messy datasets by handling missing values, duplicates, and incorrect formatting. 3. Analyze data using descriptive statistics and exploratory data analysis techniques. 4. Apply modern dataframe operations to filter, group, and aggregate information. 5. Design clear, impactful data visualizations that communicate key insights effectively. 6. Implement basic data quality checks to ensure your analysis is reliable and reproducible. Starting with core definitions and fundamental concepts, this course progresses through step-by-step written explanations, practical code snippets, and structured analytical exercises. Designed for absolute beginners, this course requires no prior data analysis experience. Start your journey into data analytics today and learn how to turn raw numbers into clear stories.