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Cancellation Policy: If you cancel your registration at least two weeks before the course is scheduled to begin, you are entitled to a full refund (minus a processing fee of $50).

In the unlikely event that Statistical Horizons LLC must cancel a seminar, we will do our best to inform you as soon as possible of the cancellation. You would then have the option of receiving a full refund of the seminar fee or a credit towards another seminar. In no event shall Statistical Horizons LLC be liable for any incidental or consequential damages that you may incur because of the cancellation.

An 8-Hour Livestream Seminar Taught by Edwin Dalmaijer, DPhil

Python is a general-purpose programming language. It is open-source, powerful, and easy to use. Because of this, Python is one of the most popular languages in the world, and it has become indispensable in data science.

In this course, we will cover various types of regression models. These are supervised statistical techniques: you give them variables and an outcome, and they will try to find the best fitting set of parameters that most closely predicts the outcome from the variables.

You will learn how to fit regression models to data, and how to use trained models for prediction. You will be introduced to multivariable and multivariate linear regression, logistic regression, and mediation analysis. To avoid over-fitting, you will also learn how to divide datasets into train and test sets, and how to implement different types of cross-validation.

The above will be implemented in scikit-learn, a Python package for machine learning. It is a powerful tool for data science, and its common interface will allow you to extend what you learn in this course to other models.