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IBM: Guided Project: Predict World Cup Soccer Results with ML

In this beginner-friendly, hands-on guided project, develop your data science and machine learning skills in under an hour by building a prediction model for the 2022 FIFA World Cup. Perfect for anyone interested in learning more about prediction models.

Guided Project: Predict World Cup Soccer Results with ML
1 weeks
1 hours per week
Self-paced
Progress at your own speed
This course is archived
Guided Project: Predict World Cup Soccer Results with ML

About this course

Skip About this course

Machine learning has changed the game for sports predictions. Popular Python libraries like LIME and SHAP are used to interpret and explain models. Even if you are not a soccer fan or working in the sports industry, machine learning skills are in demand in many industries. The skills needed to import and use data to create predictive models are both practical and valuable.

In this hands-on guided project, you’ll develop practical Python, pandas, numpy, sklearn, seaborn, matplotlib, seaborn, LIME, and SHAP skills to process data using the 2022 World Cup teams’ data. Then, you’ll train a model to predict the outcome of the group stages.

After completing this project, you will have practical experience working with Python machine-learning tools.

Get started fast. This hands-on guided project uses a browser-accessible development environment with the technologies and libraries you need, preinstalled—including the Python IDE—saving you setup time and complications. Also, note that this platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer, or Safari.

At a glance

  • Institution: IBM
  • Subject: Computer Science
  • Level: Introductory
  • Prerequisites:

    For this project, you will need:

    • Basic Python skills
    • Access to a web browser
  • Language: English
  • Video Transcript: English
  • Associated skills:Seaborn, Development Environment, Predictive Modeling, Matplotlib, Microsoft Internet Explorer, Pandas (Python Package), NumPy, Data Science, Machine Learning, Scikit-learn (Machine Learning Library), Firefox, Forecasting, Python (Programming Language)

What you'll learn

Skip What you'll learn

After completing this hands-on guided project, you’ll be able to:

  • Choose and collect the data to import into the project
  • Clean data for a machine learning project
  • Understand objects needed for a machine learning project
  • Use machine learning to predict sports games
  • Analyze machine learning model using LIME and SHAP

Who can take this course?

Unfortunately, learners residing in one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this course in all locations. edX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.

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