Football: More than a Game (Coursera)

Football: More than a Game (Coursera)

Explore the world of football (soccer), the money, the rivalries, the trends, the past, the present, the men’s game, the women's game and the real issues. Whether you love it, hate it or try to ignore it – join us as we go behind the scenes to examine why football is more than just a game.

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

From street soccer to multi-million dollar transfers, from the men’s game to the women’s, from the global to the local, from the beaches of Brazil to the fight against poverty this online course looks beyond the pitch, to explore football’s role in society and possibly a community near you.

Syllabus

WEEK 1
Football: History, myths and power
This week considers the past, football myths and how history can help us understand football today. We will explore an extraordinary football journey not only taking in major milestones along the way, but getting a feel for how history can help us understand the present as well as the past.

WEEK 2
The global spectacle of football
We now move on to consider the game to-day and how it has grown into a global spectacle. Is football truly a global game? This week is a little bit more conceptual because we as ask you to think about some concepts – global, local and international and how these are helpful in explaining the growth of world football. We need to know not only what countries are involved but also who (which people) are involved and where the real power in football lies?

WEEK 3
Great football clubs, nations and matches that changed the world
It is impossible to cover every great club and rivalry. Nonetheless, in Week 3 we will look at football wealth, rivalry, community, and matches that made a difference.

WEEK 4
The FIFA World Cup – Who are the champions of the world?
We take a look at three different competitions, the Men’s World Cup, the Women’s World Cup and the Homeless World Cup.

WEEK 5
Football for International Development, Diplomacy and Peace
In week five we examine how football helps with international development, diplomacy and peace. We continue to advance the case for football delivering non-football outcomes. As a form of soft power football is often able to broker moments of normality within tense situations or periods of conflict. The activities associated with this week introduce you to issues of development, diplomacy, and conflict resolution. You are asked to consider whether football can act as a resource of hope. You are asked to continue thinking about football delivering Non-Football Outcomes.

WEEK 6
Football finances, ownership and review
This final week introduces you to some issues around football finance and governance It also provides you with an opportunity to consider why you think football is more than a game.

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

Related Courses

Introduction to Big Data (Coursera) Coursera
University of California, San Diego

Introduction to Big Data (Coursera)

Interested in increasing your knowledge of the Big Data landscape? This course is for those new to data science and interested in understanding why the Big Data Era has come to be. It is for those who want to become conversant with the terminology and the core concepts behind big data problems, applications, and systems. It is for those who want to start thinking about how Big Data might be useful in their business or career. It provides an introduction to one of the most common frameworks, Hadoop, that has made big data analysis easier and more accessible -- increasing the potential for data to transform our world!

Jun 1st 2026
3 Weeks
Big Data Integration and Processing (Coursera) Coursera
University of California, San Diego

Big Data Integration and Processing (Coursera)

At the end of the course, you will be able to: Retrieve data from example database and big data management systems; Describe the connections between data management operations and the big data processing patterns needed to utilize them in large-scale analytical applications; Identify when a big data problem needs data integration; Execute simple big data integration and processing on Hadoop and Spark platforms.

Jun 1st 2026
5-12 Weeks
Data Analysis Tools (Coursera) Coursera
Wesleyan University

Data Analysis Tools (Coursera)

In this course, you will develop and test hypotheses about your data. You will learn a variety of statistical tests, as well as strategies to know how to apply the appropriate one to your specific data and question. Using your choice of two powerful statistical software packages (SAS or Python), you will explore ANOVA, Chi-Square, and Pearson correlation analysis. This course will guide you through basic statistical principles to give you the tools to answer questions you have developed. Throughout the course, you will share your progress with others to gain valuable feedback and provide insight to other learners about their work.

Jun 1st 2026
4 Weeks
Python Project for Data Science (Coursera) Coursera
IBM

Python Project for Data Science (Coursera)

This mini-course is intended to for you to demonstrate foundational Python skills for working with data. The completion of this course involves working on a hands-on project where you will develop a simple dashboard using Python. This course is part of the IBM Data Science Professional Certificate and the IBM Data Analytics Professional Certificate.

Jun 4th 2026
1 Week
Dealing With Missing Data (Coursera) Coursera
University of Maryland, College Park

Dealing With Missing Data (Coursera)

This course will cover the steps used in weighting sample surveys, including methods for adjusting for nonresponse and using data external to the survey for calibration. Among the techniques discussed are adjustments using estimated response propensities, poststratification, raking, and general regression estimation. Alternative techniques for imputing values for missing items will be discussed. For both weighting and imputation, the capabilities of different statistical software packages will be covered, including R®, Stata®, and SAS®.

Jun 1st 2026
4 Weeks
Meaningful Marketing Insights (Coursera) Coursera
Emory University

Meaningful Marketing Insights (Coursera)

With marketers are poised to be the largest users of data within the organization, there is a need to make sense of the variety of consumer data that the organization collects. Surveys, transaction histories and billing records can all provide insight into consumers’ future behavior, provided that they are interpreted correctly. In Introduction to Marketing Analytics, we introduce the tools that learners will need to convert raw data into marketing insights. The included exercises are conducted using Microsoft Excel, ensuring that learners will have the tools they need to extract information from the data available to them.

Jun 1st 2026
5-12 Weeks
Reproducible Research (Coursera) Coursera
Johns Hopkins University

Reproducible Research (Coursera)

This course focuses on the concepts and tools behind reporting modern data analyses in a reproducible manner. Reproducible research is the idea that data analyses, and more generally, scientific claims, are published with their data and software code so that others may verify the findings and build upon them. The need for reproducibility is increasing dramatically as data analyses become more complex, involving larger datasets and more sophisticated computations.

Jun 1st 2026
4 Weeks
Social Media Data Analytics (Coursera) Coursera
University of Washington

Social Media Data Analytics (Coursera)

Learner Outcomes: After taking this course, you will be able to: utilize various Application Programming Interface (API) services to collect data from different social media sources such as YouTube, Twitter, and Flickr; process the collected data - primarily structured - using methods involving correlation, regression, and classification to derive insights about the sources and people who generated that data; analyze unstructured data - primarily textual comments - for sentiments expressed in them; use different tools for collecting, analyzing, and exploring social media data for research and development purposes.

Jun 1st 2026
4 Weeks
Managing Data Analysis (Coursera) Coursera
Johns Hopkins University

Managing Data Analysis (Coursera)

This one-week course describes the process of analyzing data and how to manage that process. We describe the iterative nature of data analysis and the role of stating a sharp question, exploratory data analysis, inference, formal statistical modeling, interpretation, and communication. In addition, we will describe how to direct analytic activities within a team and to drive the data analysis process towards coherent and useful results.

Jun 1st 2026
1 Week
Analyze Data to Answer Questions (Coursera) Coursera
Google

Analyze Data to Answer Questions (Coursera)

This is the fifth course in the Google Data Analytics Certificate. These courses will equip you with the skills needed to apply to introductory-level data analyst jobs. In this course, you’ll explore the “analyze” phase of the data analysis process. You’ll take what you’ve learned to this point and apply it to your analysis to make sense of the data you’ve collected. You’ll learn how to organize and format your data using spreadsheets and SQL to help you look at and think about your data in different ways. You’ll also find out how to perform complex calculations on your data to complete business objectives.

Jun 2nd 2026
4 Weeks
Exploratory Data Analysis (Coursera) Coursera
Johns Hopkins University

Exploratory Data Analysis (Coursera)

This course covers the essential exploratory techniques for summarizing data. These techniques are typically applied before formal modeling commences and can help inform the development of more complex statistical models. Exploratory techniques are also important for eliminating or sharpening potential hypotheses about the world that can be addressed by the data.

Jun 1st 2026
4 Weeks
The Data Scientist's Toolbox (Coursera) Coursera
Johns Hopkins University

The Data Scientist's Toolbox (Coursera)

In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio.

Jun 1st 2026
4 Weeks