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Intermediate Regression with statsmodels in Python

Intermediate
4.5+
16 reviews
Updated 12/2024
Learn to perform linear and logistic regression with multiple explanatory variables.
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PythonProbability & Statistics4 hours14 videos52 exercises4,300 XP11,000Statement of Accomplishment

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Course Description

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 course, you’ll build on the skills you gained in "Introduction to Regression in Python with statsmodels", as you learn about linear and logistic regression with multiple explanatory variables. 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.

Prerequisites

Introduction to Regression with statsmodels in Python
1

Parallel Slopes

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2

Interactions

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3

Multiple Linear Regression

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4

Multiple Logistic Regression

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Intermediate Regression with statsmodels in Python
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*4.5
from 16 reviews
56%
38%
6%
0%
0%
  • Li D.
    about 2 months

    Great

  • Nikolaos C.
    3 months

    Excellent course. It delves deep into the details of all calculations involved and how to recreate them in python. This gives a great insight into the methodology.

  • Ana U.
    11 months

    This is an excellent course. The instructor and the content of the course are extraordinary. The exercises are challenging and are created to stimulate the desire to learn more about the topic. I learned and enjoyed a great deal.

  • Noel C.
    12 months

    The best teacher in DataCamp

  • Ildar K.
    about 1 year

    i hope that this course would help to furhter career, 10x!

"Great"

Li D.

"Excellent course. It delves deep into the details of all calculations involved and how to recreate them in python. This gives a great insight into the methodology."

Nikolaos C.

"This is an excellent course. The instructor and the content of the course are extraordinary. The exercises are challenging and are created to stimulate the desire to learn more about the topic. I learned and enjoyed a great deal."

Ana U.

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