Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
7 Hour(s) 10 Minute(s)
Language
English
Taught by
Najib Mozahem
Certificate
- Available
- *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Rating
Course Overview
An Introduction to Predictive Analytics for Data Scientists
Included in this course is an e-book and a set of slides. The purpose of the course is to introduce the students to regression techniques. The course covers linear regression, logistic regression and count model regression. The theory behind each of these three techniques is described in an intuitive and non-mathematical way. Students will learn when to use each of these three techniques, how to test the assumptions, how to build models, how to assess the goodness-of-fit of the models, and how to interpret the results. The course does not assume the use of any specific statistical software. Therefore, this course should be of use to anyone intending on applying regression techniques no matter which software they use. The course also walks students through three detailed case studies.
Course Content
- 15 section(s)
- 89 lecture(s)
- Section 1 Simple Linear Regression
- Section 2 Multiple linear regression
- Section 3 Linear Regression: Binary, Categorical, and Quadratic Variables
- Section 4 Linear Regression: Checking Model Fit and Assumptions
- Section 5 Linear Regression Case Study
- Section 6 Logistic Regression: Contingency Tables
- Section 7 Logistic Regression Models
- Section 8 Logistic Regression: Prediction and Model Fit
- Section 9 Logistic Regression Case Study
- Section 10 Count Models: Count Tables
- Section 11 Poisson Regression
- Section 12 Other Count Models
- Section 13 Prediction
- Section 14 Count Model Case Study
- Section 15 Conclusion
What You’ll Learn
- Understand what regression is
- Build linear regression models
- Build logistic regression models
- Build count models
- Interpret regression results
- Visualise the results
- Test model assumptions
Skills covered in this course
Reviews
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IIrshad Pathan
Najib did a great job on explaining the different regression techniques. A topic like this can be dense, however Najib was able to break it into many sections and clearly explain the different regression techniques and pairing it with case studies. I would recommend this course to anyone who is looking for an introduction to regression techniques.
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MMerel Bakker
Very easy and cleary explained. Did a much better job than a very pricy course I followed in the past ;)
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GGal Zohar
Very clear explanations. Makes you wonder but at rlthe same time you finally understand the material easy. The theoretical followed by a practical explanations is great
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HHamish
This has been an excellent course, with the right level of explanation. It will help you make an informed choice in what model to use. I tutor maths and stats; this has certainly completed some of the gaps in my understanding. Highly recommended.
