Introduction to Data Analysis Using Excel for Researchers
Enhance your data analysis skills with Excel. Learn how to work with textual and numerical data, perform calculations, generate dates, and create visualizations. This course is perfect for beginners in data analysis and those interested in the field of data science.
What you’ll learn
- Work with Excel Workbooks
- Data Analysis Concepts
- Work with Textual Data
- Work with Numerical Data
- Perform Calculations on Data
- Generate Dates
- Perform Calculations on Dates
- Use the VLOOKUP Function
- Create Charts and Visualizations
Build Strong Excel Skills
Excel is one of the most widely used solutions for analyzing and visualizing data. It now includes tools that enable the analysis of more data, with improved visualizations and more sophisticated logics. Excel is the world’s most popular data analysis tool. Companies and institutions worldwide use it to transform mountains of raw data into clear insights. Strong Excel skills can open new career paths, make you more employable in various industries, and save hours in your daily tasks.
Practice Using Excel with Practical Datasets
In this course, you’ll develop employable data analyst skills, starting with the Excel basics, what it can do, and the data analysis steps you should follow.
The sections begin by exploring data; navigate your worksheet and trim and classify your data types. You’ll even work with real-world data to use your new-found Excel skills to analyze what makes a successful project.
Learn How to Use VLOOKUP
Other sections in this course will teach you how to prepare your data by extracting text, preparing date data, and which Excel formulas can help. You’ll learn to use the most important function in Excel: VLOOKUP to combine data from different sources.
These Excel skills, functions, and time-saving shortcuts can be applied to any industry, whether you’re looking to move to a career in data analysis, or looking to improve your skills in marketing, finance, HR, logistics, and more.
Who this course is for:
- Beginners in Data Analysis
- Enthusiasts in the Field of Data Science
- Social Sciences Researchers
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