EdX

Excel for Everyone: Core Foundations (edX)

Excel for Everyone: Core Foundations (edX)

Learn Excel fundamentals including data wrangling, spreadsheet management, and basic data analysis. This introductory Excel course will equip you with a strong foundational knowledge of Excel to organize, analyze and work with data. You will develop essential Excel skills, such as simple data wrangling and managing spreadsheets, along with a foundational understanding of business data analysis.

Class Deals by MOOC List - Click here and see EdX's Active Discounts, Deals, and Promo Codes.

The course is designed for those with little or no functional knowledge of Excel, as well as those who regularly use Excel at a basic level, but wish to enhance their skills. From basic operations to an introduction to more advanced techniques, within six weeks you’ll gain the confidence to navigate the Excel interface, master essential spreadsheet functions, perform calculations and produce creative charts and graphs from your data, while building an aptitude for data analysis that is critical to the success of any organization.
This course is part of the Excel for Everyone Professional Certificate.

What you'll learn

  • Excel fundamentals.
  • Data entry and editing using various formats.
  • Performing calculations using formulas and functions.
  • How to format and optimize spreadsheets.
  • How to manage spreadsheets using Filter and sort table data capabilities.
  • Previewing and printing.
  • Effective data visualization using basic charts.
Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

RShiny for Everyone (edX) EdX
Davidson College,DavidsonX

RShiny for Everyone (edX)

Use R’s Shiny package to create data-driven, interactive web applications. In this course, you will use R Shiny to create an interactive web application that highlights the biodiversity of America’s National Parks. Your application will feature an interactive map, biodiversity calculator, trail journal and species images. Using R Shiny, you will expand your data analysis and visualization skills while developing your workflow through web application deployment.

Self Paced
Self-Paced
Data Science: Capstone (edX) EdX
HarvardX,Harvard University

Data Science: Capstone (edX)

Show what you’ve learned from the Professional Certificate Program in Data Science. To become an expert data scientist you need practice and experience. By completing this capstone project you will get an opportunity to apply the knowledge and skills in R data analysis that you have gained throughout the series. This final project will test your skills in data visualization, probability, inference and modeling, data wrangling, data organization, regression, and machine learning.

Self Paced
Self-Paced
Data Science: Wrangling (edX) EdX
HarvardX,Harvard University

Data Science: Wrangling (edX)

Learn to process and convert raw data into formats needed for analysis. In this course, we cover several standard steps of the data wrangling process like importing data into R, tidying data, string processing, HTML parsing, working with dates and times, and text mining. Rarely are all these wrangling steps necessary in a single analysis, but a data scientist will likely face them all at some point.

Self Paced
Self-Paced
Analyzing Data with Excel (edX) EdX
IBM

Analyzing Data with Excel (edX)

Build the fundamental knowledge required to use Excel spreadsheets to perform basic data analysis. The course covers the basic workings and key features of Excel to help students analyze their data. This course provides students with the fundamental knowledge required to use Excel spreadsheets to perform basic data analysis.The course consists of several videos, demos, examples, and hands-on labs to help you learn, and ends with a final assignment project which will help you put what you have learned into practice.

Self Paced
Self-Paced
Introductory Statistics : Analyzing Data Using Graphs and Statistics (edX) EdX
Seoul National University,SNUx

Introductory Statistics : Analyzing Data Using Graphs and Statistics (edX)

This course teaches basic statistical concepts and explores many compelling applications of statistical methods using real-life applications of Statistics. Why do we study statistics? The field of statistics provides professionals and scientists withconceptual foundations and useful techniques for evaluating ideas, testing theories, and - ultimately -uncovering the truth in any situation.

Self Paced
Self-Paced
Case Studies in Functional Genomics (edX) EdX
HarvardX,Harvard University

Case Studies in Functional Genomics (edX)

Perform RNA-Seq, ChIP-Seq, and DNA methylation data analyses, using open source software, including R and Bioconductor. We will explain how to perform the standard processing and normalization steps, starting with raw data, to get to the point where one can investigate relevant biological questions.

Self Paced
Self-Paced
Data Analytics and Visualization Capstone Project (edX) EdX
IBM

Data Analytics and Visualization Capstone Project (edX)

Accelerate the knowledge you gain from previous courses in the IBM Data Analyst Professional Certificate program. Assume the role of an Associate Data Analyst and use various skills and techniques on real-world datasets to accomplish a task. This course provides students with the opportunity to assume the role of an Associate Data Analyst who has recently joined an organization. In this role, you will use Data Analytics skills and techniques on real-world datasets to complete a business task.

Self Paced
Self-Paced
Data Science: Inference and Modeling (edX) EdX
HarvardX,Harvard University

Data Science: Inference and Modeling (edX)

Learn inference and modeling, two of the most widely used statistical tools in data analysis. Statistical inference and modeling are indispensable for analyzing data affected by chance, and thus essential for data scientists. In this course, you will learn these key concepts through a motivating case study on election forecasting.

Self Paced
Self-Paced
Observation Theory: Estimating the Unknown (edX) EdX
Delft University of Technology,DelftX

Observation Theory: Estimating the Unknown (edX)

Learn how to estimate parameters from observational data for real-world engineering applications and assess the quality of the results. Are you an engineer, scientist or technician? Are you dealing with measurements or big data, but are you unsure about how to proceed? This is the course that teaches you how to find the best estimates of the unknown parameters from noisy observations. You will also learn how to assess the quality of your results.

Self Paced
Self-Paced
Introduction to Linear Models and Matrix Algebra (edX) EdX
HarvardX,Harvard University

Introduction to Linear Models and Matrix Algebra (edX)

Learn to use R programming to apply linear models to analyze data in life sciences. Matrix Algebra underlies many of the current tools for experimental design and the analysis of high-dimensional data. In this introductory data analysis course, we will use matrix algebra to represent the linear models that commonly used to model differences between experimental units. We perform statistical inference on these differences. Throughout the course we will use the R programming language.

Self Paced
Self-Paced
Basics of Statistical Inference and Modelling Using R (edX) EdX
University of Canterbury,UCx

Basics of Statistical Inference and Modelling Using R (edX)

Learn why a statistical method works, how to implement it using R and when to apply it and where to look if the particular statistical method is not applicable in the specific situation. Basics of Statistical Inference and Modelling Using R is part one of the Statistical Analysis in R professional certificate.

Self Paced
Self-Paced
Data Processing and Analysis with Excel (edX) EdX
Rochester Institute of Technology,RITx

Data Processing and Analysis with Excel (edX)

Learn to use Excel to organize and clean data so it can be manipulated and analyzed. In this course, you will learn how to organize your data within the Microsoft Office Excel software tool. Once organized, we will discuss data cleaning. You will learn how to identify outliers and anomalies in the data, and how to identify and change data-types. Together we will develop a data analysis plan, after which we will apply analysis methods and tools, including exploratory analysis, evaluation of results, and comparison with other findings.

Self Paced
Self-Paced