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Design Effective Statistical Models to Understand Your Data

Build, interpret, and evaluate linear, logistic and polynomial regression models based on observations in your data.
DifficultyMedium12 hours
Interested in this free-access course?

Linear regression is the go-to method to rapidly understand a dataset.

Linear and logistic regression are prevailing and powerful statistical methods used in a variety of domains. They are simple to implement, yet offer a depth of analytical knowledge. What's more, they can be used both for statistical modeling and predictive analytics.

This course is designed to teach you applied linear and logistic regression by having you (yes, you!) build increasingly complex models. First, you will gain a deep understanding of the foundations before diving into linear regression. After that, we will go one step further and handle classification and nonlinear datasets. Finally, we will use regression techniques to build resilient predictive models. 

Throughout the course, we will work on real-world datasets to give you tangible, hands-on training.

Ready to go?

Learning outcomes

  • Build Linear Regression Models
  • Build Generalized Linear Models
  • Build Predictive Models

Turn it into a career

Take one of our 100% online diploma training programs, and transform your know-how into professional skills.

  • Up to 100% of your training program funded
  • Flexible start date
  • Career-focused projects
  • Individual mentoring

Contributors

Instructor

Alexis Perrier

Auteur et enseignant en Data Science, expert Machine Learning. Suivez @alexip sur Twitter.

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Last updated: 1/23/2025

License

Data

Design Effective Statistical Models to Understand Your Data

DifficultyMedium12 hours
Free-access course