Statistical Predictive Modelling and Applications

Dr Galina Andreeva, Dr Matthias Bogaert, Sofia Varypati, EdinburghX

Learn how to apply statistical modelling techniques to real-world business scenarios using Python.

In this course, you will learn three predictive modelling techniques - linear and logistic regression, and naive Bayes - and their applications in real-world scenarios.

The first half of the course focuses on linear regression. This technique allows you to model a continuous outcome variable using both continuous and categorical predictors. This technique enables you to predict product sales based on several customer variables.

In the second half of the course, you will learn about logistic regression, which is the counterpart of linear regression, when the response variable is categorical. You will also be introduced to naive Bayes; a very intuitive, probabilistic modeling technique.

What will you learn

In this course, you will:

  • Discover how predictive models influence real-world business scenarios
  • Translate business challenges into predictive modeling solutions
  • Develop experience with implementing theoretic models in Python

Dates:
  • 19 January 2021
Course properties:
  • Free:
  • Paid:
  • Certificate:
  • MOOC:
  • Video:
  • Audio:
  • Email-course:
  • Language: English Gb

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