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About this course

This course is part of the “Introduction to Data Analysis with Excel” skill path, which we designed for anyone who wants to gain the practical skills in Excel to perform data analysis and visualization, and ultimately help organizations make better informed decisions. We designed it for aspiring data professionals with little experience and learners who use basic Excel in their daily jobs and want to enhance their skills.

Lessons in this course

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What you’ll learn

You’ll learn how to do the following:

  • Import data into an Excel spreadsheet from more than one data source
  • Organize data into a spreadsheet using worksheets and tables
  • Clean, manipulate, and modify the data
  • Consolidate the data for analysis

What you’ll be able to achieve

By the end of the course, you‘ll be able to do the following:

  • Define delimiters and use them to import data
  • Import Excel files, text files, and CSV files
  • Use copy & paste and drag & drop to load files
  • Organize data with cells and ranges
  • Organize data into tables, worksheets, and workbooks
  • Apply Excel functions and formulas for organizing data
  • Find and remove duplicate data
  • Find and remove extra spaces
  • Separate data without delimiters
  • Correct inaccurate or irrelevant data
  • Update missing or incomplete data
  • Standardize the case for text
  • Standardize formats for dates
  • Standardize formats for numbers
  • Work with outliers
  • Verify clean data with visualizations
  • Manipulate headers
  • Work with the Consolidate tool
  • Merge data using copy and paste
  • Use VLOOKUP
  • Use INDEX/MATCH

Guided Project — Preparing Shark Attack Data for Analysis

In this guided project, you’ll import a shark attack dataset, organize it, and clean it so it’s ready to analyze.

You will learn how to do the following:

  • Import data into a spreadsheet from more than one data source
  • Organize data into a spreadsheet using worksheets and tables
  • Clean data by removing duplicates and irrelevant data
  • Work with missing data and inconsistent data types
  • Consolidate the data for analysis

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