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IBM

Excel Basics for Data Analysis

IBM via Coursera

Overview

Prepare for a new career with $100 off Coursera Plus
Gear up for jobs in high-demand fields: data analytics, digital marketing, and more.
Spreadsheet tools like Excel are an essential tool for working with data - whether for data analytics, business, marketing, or research. This course is designed to give you a basic working knowledge of Excel and how to use it for analyzing data.

This course is suitable for those who are interested in pursuing a career in data analysis or data science, as well as anyone looking to use Excel for data analysis in their own domain. No prior experience with spreadsheets or coding is required - all you need is a device with a modern web browser and the ability to create a Microsoft account to access Excel online at no cost. If you have a desktop version of Excel, you can also easily follow along with the course.

Throughout this course, you'll gain valuable experience working with data sets and spreadsheets. We'll start by introducing you to spreadsheets like Microsoft Excel and Google Sheets, and show you how to load data from multiple formats. From there, you'll learn how to perform basic data wrangling and cleansing tasks using functions, and expand your knowledge of data analysis through the use of filtering, sorting, and pivot tables.

There is a strong focus on practice and applied learning in this course. With each lab, you'll have the opportunity to manipulate data and gain hands-on experience using Excel. You'll learn how to clean and format your data efficiently, and convert it into a pivot table to make it more organized and readable. The final project will allow you to showcase your newly acquired data analysis skills by working with real data sets and spreadsheets.

By the end of this course, you'll have a solid foundation in using Excel for data analysis. You'll have worked with multiple data sets and spreadsheets, and will have the skills and knowledge needed to effectively clean and analyze data without having to learn any code. So let's get started!

Syllabus

  • Introduction to Data Analysis Using Spreadsheets
    • In this module, you will learn about the fundamentals of spreadsheet applications, and you will be introduced to the Excel interface and learn how to navigate your way around a worksheet and workbook.
  • Getting Started with Using Excel Speadsheets
    • In this module you will learn how to perform basic spreadsheet tasks, such as viewing, entering and editing data, and moving, copying and filling data. In addition, you will learn about the fundamentals of formulas, and learn about the most common functions used by a data analyst. Finally, you will learn how to reference data in formulas.
  • Cleaning & Wrangling Data Using Spreadsheets
    • In this module, you will learn about the importance of data quality, and you will learn how to import file data in to Excel. You will also learn about the fundamentals of data privacy. In addition, you will learn how to remove duplicate and inaccurate data, and how to remove empty rows in your data. Finally, you will learn how to deal with inconsistencies in your data and how to use the Flash Fill and Text to Columns features to help you manipulate and standardize your data.
  • Analyzing Data Using Spreadsheets
    • In this module, you will learn about the fundamentals of analyzing data using a spreadsheet, and learn how to filter and sort data. You will also learn how to use some of the most useful functions for a data analyst, and how to use the VLOOKUP and HLOOKUP reference functions. In addition, you will learn how to create pivot tables in Excel, and use several pivot table features.
  • Final Project
    • Great! You have now completed all four modules of this course. In this final module, you will be introduced to a hands-on lab where you will complete a graded assignment for cleaning and preparing data, and then analyzing data using an Excel spreadsheet. This final assignment will be graded by your peers.

Taught by

Steve Ryan and Sandip Saha Joy

Reviews

4.8 rating at Coursera based on 7185 ratings

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