This course focuses on data cleaning and processing using Copilot in Excel. It empowers you to identify and correct data errors, handle missing values and duplicates, and standardize data types. You will explore advanced text manipulation, column operations, and external data integration, leveraging Copilot for efficient data transformation. Additionally, you will design structured data workflows by developing effective prompts for Copilot, enabling you to pose clear questions that guide your analysis. Through practical modules, you’ll develop skills in data organization, error identification, and cleaning strategies. By the end of this course, you will enhance data accuracy and reliability, ensuring your datasets are analysis-ready. Elevate your data processing capabilities and gain a competitive edge in data-driven decision-making.
Data Cleaning & Processing with Copilot in Excel
This course is part of Microsoft Excel Professional Certificate Professional Certificate
Instructor: Microsoft
Included with 
Recommended experience
What you'll learn
Identify and address common data errors using Copilot in Excel.
Apply comprehensive data cleaning techniques to prepare datasets for analysis.
Manipulate and transform data efficiently with Copilot.
Implement data organization strategies for improved analysis readiness.
Skills you'll gain
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There are 5 modules in this course
This module introduces basic data preparation techniques and error identification methods using Copilot in Excel. Learners will learn to identify and address common data errors and transform data for analysis.
What's included
8 readings4 assignments
In this module, learners will develop essential skills in data preparation using Copilot in Excel, focusing on identifying and addressing missing values, removing duplicates, and applying manual and automated imputation techniques. Through videos, readings, hands-on activities, and quizzes, learners will gain practical experience ensuring data integrity and readiness for analysis. For example, a healthcare analyst might use these techniques to clean patient records, ensuring accurate and complete data for a clinical study. By the end of the module, learners will be proficient in transforming raw data into reliable datasets for meaningful analysis.
What's included
2 readings4 assignments
This module focuses on converting and standardizing data types using Excel Copilot, ensuring consistency and accuracy in datasets. Learners will learn to convert data to the desired formats and standardize data for analysis.
What's included
1 reading4 assignments
This module covers techniques for manipulating text data and performing column operations using Excel Copilot, ensuring efficient data organization and improved readability.
What's included
1 reading4 assignments
This module focuses on designing structured and logical data analysis workflows by developing effective prompts for Excel Copilot. Learners will learn to pose clear and precise questions to Copilot to guide their data analysis processes.
What's included
3 readings3 assignments1 peer review
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