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Overview
Context
Linear regression and logistic regression are the two most widely used statistical models and act like master keys, unlocking the secrets hidden in datasets.
In this Intermediate Regression with statsmodels in Python course offered by Data Camp, you’ll build on the skills you gained in "Introduction to Regression in Python with statsmodels".
Through hands-on exercises, you’ll explore the relationships between variables in real-world datasets, Taiwan house prices and customer churn modeling, and more.
By the end of this course, you’ll know how to include multiple explanatory variables in a model, discover how interactions between variables affect predictions, and understand how linear and logistic regression work.
Programme Structure
Chapters
- Parallel Slopes
- Interactions
- Multiple Linear Regression
- Multiple Logistic Regression
Key information
Duration
- Part-time
- 1 days
Start dates & application deadlines
You can apply for and start this programme anytime.
Language
English
Delivered
Online
Campus Location
- New York City, United States
Disciplines
Data Science & Big Data View 467 other Short Courses in Data Science & Big Data in United StatesWhat students do after studying
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Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
- PREREQUISITES: Introduction to Regression with statsmodels in Python
- This course is aimed at individuals interested in data science
Tuition Fees
Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
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International Applies to you
Applies to youNon-residentsFree - Out-of-StateFree
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Domestic
Applies to youIn-StateFree
Additional Details
This course can be accessed for free with the Data Camp Premium or Teams subscriptions
Funding
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