Data Cleaning with Python for Data Analysts

Course overview

This training provides you with practical knowledge in the field of data cleaning. You will learn to categorize typical tasks confidently, apply suitable methods and tools, and prepare results in a comprehensible manner. The focus is on practical applications from the fields of Python and Data Science that will support you in your role as a Data Analyst or in comparable professional tasks. Data fundamentals and analysis objectives in the context of data cleaning distinguish relevant data sources, data types, and analysis questions professionally assess data structures, data quality, and significance derive key figures, metrics, and evaluation objectives from requirements plan and document analysis processes in a comprehensible manner Python for data preparation and evaluation specifically use Python for queries, calculations, or analysis steps clean, transform, and prepare data for evaluations implement recurring work steps in a structured and comprehensible manner prepare results for verification and professional interpretation Visualization, reporting, and decision support present evaluation results in tables, charts, or dashboards structure reports appropriately for the target audience and highlight key messages derive anomalies, patterns, and deviations from data use data analyses as a basis for operational or strategic decisions Transfer to data-related tasks as a Data Analyst categorize typical tasks and requirements as a Data Analyst document and present professional results appropriately for the audience reflect on work methods and transfer them to your own professional situations derive the next implementation steps for everyday work in a structured manner This training helps you to handle typical tasks in the field of data cleaning more safely and efficiently. You will combine professional knowledge with practical methods and tools from the fields of Python and Data Science. This will strengthen your confidence in your role as a Data Analyst and allow you to apply the content directly in your professional life.

Upcoming dates

• 2026-08-09T22:00:00.000Z · 2027-01-24T23:00:00.000Z · Recklinghausen, Westfalen · Blended Learning
• 2026-08-09T22:00:00.000Z · 2027-01-24T23:00:00.000Z · Eberswalde · Blended Learning
• 2026-08-09T22:00:00.000Z · 2027-01-24T23:00:00.000Z · Berlin · Blended Learning
• 2026-08-09T22:00:00.000Z · 2026-11-01T23:00:00.000Z · Erfurt · Blended Learning
• 2026-08-09T22:00:00.000Z · 2027-01-24T23:00:00.000Z · Erfurt · Blended Learning