Data Cleaning and Preparation

О курсе

Learn how to clean, structure, and prepare datasets for analysis in this foundational course within the Data Analytics Skill Path. You will develop essential competencies, including handling missing values, converting data types to enforce schemas, standardizing text fields, correcting structural and formatting issues, and identifying and removing duplicate records. Through hands-on practice with Power BI, Excel with Copilot, and Python, you will learn to transform inconsistent raw data into accurate, reliable, analysis-ready datasets. This course integrates expertise from Microsoft and IBM, offering multiple perspectives on data preparation across both business intelligence and programmatic environments. You will progress from identifying and addressing data quality issues in Power BI, to applying schema alignment and automated error detection in Excel, and finally to manipulating, profiling, and deduplicating datasets using Python and Pandas. The curriculum blends conceptual understanding with practical exercises, helping you build confidence in applying cleaning techniques across tools commonly used in industry. Perfect for aspiring analysts, data professionals, and learners seeking strong foundational skills in data cleaning, transformation, and preparation across modern analytics platforms.

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