Coursera

Introduction to Data Analysis Using Excel (Coursera)

Offered by Rice University,

The use of Excel is widespread in the industry. It is a very powerful data analysis tool and almost all big and small businesses use Excel in their day to day functioning. This course is designed to give you a working knowledge of Excel with the aim of getting to use it for more advance topics in Business Statistics. The course is designed keeping in mind two kinds of learners - those who have very little functional knowledge of Excel and those who use Excel regularly but at a peripheral level and wish to enhance their skills.

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

The course takes you from basic operations such as reading data into excel using various data formats, organizing and manipulating data, to some of the more advanced functionality of Excel. All along, Excel functionality is introduced using easy to understand examples which are demonstrated in a way that learners can become comfortable in understanding and applying them.
Course 1 of 5 in the Business Statistics and Analysis Specialization.

Syllabus

WEEK 1
Introduction to Spreadsheets
Introduction to spreadsheets, reading data, manipulating data. Basic spreadsheet operations and functions.
In this module, you will be introduced to the use of Excel spreadsheets and various basic data functions of Excel.
Topics covered include:
• Reading data into Excel using various formats
• Basic functions in Excel, arithmetic as well as various logical functions
• Formatting rows and columns
• Using formulas in Excel and their copy and paste using absolute and relative referencing

WEEK 2
Spreadsheet Functions to Organize Data
Introduction to some more useful functions such as the IF, nested IF, VLOOKUP and HLOOKUP functions in Excel.
This module introduces various Excel functions to organize and query data. Learners are introduced to the IF, nested IF, VLOOKUP and the HLOOKUP functions of Excel.
Topics covered include:
• IF and the nested IF functions
• VLOOKUP and HLOOKUP
• The RANDBETWEEN function

WEEK 3
Introduction to Filtering, Pivot Tables, and Charts
Introduction to the Data filtering capabilities of Excel, the construction of Pivot Tables to organize data and introduction to charts in Excel.
This module introduces various data filtering capabilities of Excel. You’ll learn how to set filters in data to selectively access data. A very powerful data summarizing tool, the Pivot Table, is also explained and we begin to introduce the charting feature of Excel.
Topics covered include:
• VLOOKUP across worksheets
• Data filtering in Excel
• Use of Pivot tables with categorical as well as numerical data
• Introduction to the charting capability of Excel

WEEK 4
Advanced Graphing and Charting
Constructing various Line, Bar and Pie charts. Using the Pivot chart features of Excel. Understanding and constructing Histograms and Scatterplots.
This module explores various advanced graphing and charting techniques available in Excel. Starting with various line, bar and pie charts we introduce pivot charts, scatter plots and histograms. You will get to understand these various charts and get to build them on your own.
Topics covered include
• Line, Bar and Pie charts
• Pivot charts
• Scatter plots
• Histograms

Go to Class

MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Coursera

Duke University

Introduction to Probability and Data with R (Coursera)

Statistics & Data Analysis Data Science

This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule. You will examine various types of sampling methods, and discuss how such methods can impact the scope of inference. A variety of exploratory data analysis techniques will be covered, including numeric summary statistics and basic data visualization.

Jun 22nd 2026

5-12 Weeks

Statistics Probability Inference

Coursera

University of California, San Diego

Big Data Modeling and Management Systems (Coursera)

Statistics & Data Analysis Data Science

Once you’ve identified a big data issue to analyze, how do you collect, store and organize your data using Big Data solutions? In this course, you will experience various data genres and management tools appropriate for each. You will be able to describe the reasons behind the evolving plethora of new big data platforms from the perspective of big data management systems and analytical tools.

Jun 22nd 2026

5-12 Weeks

Big Data Data Management Data Modeling

Coursera

University of Michigan

Introduction to Data Science in Python (Coursera)

CS: Software Engineering Statistics & Data Analysis

This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library. The course will introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as groupby, merge, and pivot tables effectively. By the end of this course, students will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analyses.

Jun 22nd 2026

4 Weeks

Python Data Analysis Data Science

Coursera

Universidad Nacional Autónoma de México

Introducción a Data Science: Programación Estadística con R (Coursera)

Statistics & Data Analysis Data Science

Este curso te proporcionará las bases del lenguaje de programación estadística R, la lengua franca de la estadística, el cual te permitirá escribir programas que lean, manipulen y analicen datos cuantitativos. Te explicaremos la instalación del lenguaje; también verás una introducción a los sistemas base de gráficos y al paquete para graficar ggplot2, para visualizar estos datos. Además también abordarás la utilización de uno de los IDEs más populares entre la comunidad de usuarios de R, llamado RStudio.

Jun 22nd 2026

4 Weeks

Data Analysis Data Science R Language

Coursera

University of Washington

Data Manipulation at Scale: Systems and Algorithms (Coursera)

Statistics & Data Analysis Data Science

Data analysis has replaced data acquisition as the bottleneck to evidence-based decision making --- we are drowning in it. Extracting knowledge from large, heterogeneous, and noisy datasets requires not only powerful computing resources, but the programming abstractions to use them effectively. The abstractions that emerged in the last decade blend ideas from parallel databases, distributed systems, and programming languages to create a new class of scalable data analytics platforms that form the foundation for data science at realistic scales.

Jun 22nd 2026

4 Weeks

Algebra Algorithms Databases

Coursera

University of Illinois at Urbana-Champaign

Pattern Discovery in Data Mining (Coursera)

Statistics & Data Analysis Data Science

Learn the general concepts of data mining along with basic methodologies and applications. Then dive into one subfield in data mining: pattern discovery. Learn in-depth concepts, methods, and applications of pattern discovery in data mining. We will also introduce methods for data-driven phrase mining and some interesting applications of pattern discovery. This course provides you the opportunity to learn skills and content to practice and engage in scalable pattern discovery methods on massive transactional data, discuss pattern evaluation measures, and study methods for mining diverse kinds of patterns, sequential patterns, and sub-graph patterns.

Jun 22nd 2026

4 Weeks

Algorithms Data Mining Data Analysis

Coursera

Johns Hopkins University

Bioconductor for Genomic Data Science (Coursera)

Statistics & Data Analysis Data Science

Learn to use tools from the Bioconductor project to perform analysis of genomic data. This is the fifth course in the Genomic Big Data Specialization from Johns Hopkins University.

Jun 22nd 2026

4 Weeks

Bioinformatics Data Analysis Data Science

Coursera

University of Virginia

Marketing Analytics (Coursera)

Marketing & Communication Business

Organizations large and small are inundated with data about consumer choices. But that wealth of information does not always translate into better decisions. Knowing how to interpret data is the challenge -- and marketers in particular are increasingly expected to use analytics to inform and justify their decisions. Marketing analytics enables marketers to measure, manage and analyze marketing performance to maximize its effectiveness and optimize return on investment (ROI). Beyond the obvious sales and lead generation applications, marketing analytics can offer profound insights into customer preferences and trends, which can be further utilized for future marketing and business decisions.

Jun 22nd 2026

5-12 Weeks

Marketing Regression Data Analysis

Coursera

Johns Hopkins University

Statistical Inference (Coursera)

Statistics & Data Analysis Data Science

Statistical inference is the process of drawing conclusions about populations or scientific truths from data. There are many modes of performing inference including statistical modeling, data oriented strategies and explicit use of designs and randomization in analyses. Furthermore, there are broad theories (frequentists, Bayesian, likelihood, design based, …) and numerous complexities (missing data, observed and unobserved confounding, biases) for performing inference.

Jun 22nd 2026

4 Weeks

Statistics Probability Data Analysis

Coursera

University of Colorado System

Business Intelligence Concepts, Tools, and Applications (Coursera)

Statistics & Data Analysis Data Science

This is the fourth course in the Data Warehouse for Business Intelligence specialization. Ideally, the courses should be taken in sequence. In this course, you will gain the knowledge and skills for using data warehouses for business intelligence purposes and for working as a business intelligence developer. You’ll have the opportunity to work with large data sets in a data warehouse environment and will learn the use of MicroStrategy's Online Analytical Processing (OLAP) and Visualization capabilities to create visualizations and dashboards.

Jun 22nd 2026

5-12 Weeks

Data Analysis Decision Making Business Intelligence

Coursera

ESSEC Business School

Foundations of strategic business analytics (Coursera)

Management & Leadership Business

Who is this course for? This course is designed for students, business analysts, and data scientists who want to apply statistical knowledge and techniques to business contexts. For example, it may be suited to experienced statisticians, analysts, engineers who want to move more into a business role. You will find this course exciting and rewarding if you already have a background in statistics, can use R or another programming language and are familiar with databases and data analysis techniques such as regression, classification, and clustering.

Jun 22nd 2026

4 Weeks

Data Analysis Analytics Presentations

Coursera

University of Illinois at Urbana-Champaign

Text Retrieval and Search Engines (Coursera)

Statistics & Data Analysis Data Science

Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. Text data are unique in that they are usually generated directly by humans rather than a computer system or sensors, and are thus especially valuable for discovering knowledge about people’s opinions and preferences, in addition to many other kinds of knowledge that we encode in text.

Jun 22nd 2026

5-12 Weeks

Machine Learning Search Data Mining