Statistical Predictive Modelling and Applications
Predictive Analytics 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 you'll learn
- Discover how predictive models influence real-world business scenarios
- Translate business challenges into predictive modeling solutions
- Develop experience with implementing theoretic models in Python
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| Rating | Not enough ratings |
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| Length | 6 weeks |
| Effort | 8 - 10 hours per week |
| Starts | On Demand (Start anytime) |
| Cost | $300 |
| From | EdinburghX, The University of Edinburgh via edX |
| Instructors | Dr Galina Andreeva, Dr Matthias Bogaert, Sofia Varypati, Obinna Unigwe |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Business Data Science |
| Tags | Business & Management Data Analysis & Statistics |
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| Rating | Not enough ratings |
|---|---|
| Length | 6 weeks |
| Effort | 8 - 10 hours per week |
| Starts | On Demand (Start anytime) |
| Cost | $300 |
| From | EdinburghX, The University of Edinburgh via edX |
| Instructors | Dr Galina Andreeva, Dr Matthias Bogaert, Sofia Varypati, Obinna Unigwe |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Business Data Science |
| Tags | Business & Management Data Analysis & Statistics |
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