# Regression Analysis for Business Managers in Python and R

Learn how to use Linear & Logistic Regressions by solving 2 Business Case studies in Python & R. Code templates included

Regression analysis is the most common tool at the disposal of anyone looking to analyze data. If you are looking to derive meaning insights from your data, then this course is for you.

What you’ll learn

• Linear Regression.
• Logistic Regression.
• Pricing.
• Churn drivers.
• Data Manipulation.
• R and Python.

Course Content

• Introduction –> 5 lectures • 15min.
• Linear Regression – Intuition –> 13 lectures • 43min.
• Linear Regression – Python –> 14 lectures • 54min.
• Linear Regression – R –> 15 lectures • 1hr 3min.
• Logistic Regression – Intuition –> 9 lectures • 31min.
• Logistic Regression – Python –> 14 lectures • 44min.
• Logistic Regression – R –> 12 lectures • 45min.
• Bonus lecture –> 1 lecture • 1min. Requirements

• Basic math: mean, median, standard deviation.

Regression analysis is the most common tool at the disposal of anyone looking to analyze data. If you are looking to derive meaning insights from your data, then this course is for you.

3 reasons this course is unique:

You learn not only techniques, but you also learn about Business. The intuition tutorials have their beginning dedicated to explaining to you the relevance of the business problem. By the end of the course, you will be able to discuss matters with your stakeholders related to Pricing or Customer Churn.

Real-life experience. Coding a Regression is a matter of just a couple of lines of code. However, life is not that simple. Almost always, you get a dirty dataset that you need to transform and manipulate to make it a usable and useful dataset. The practice tutorials mirror that experience. We will go through standard techniques to:

1. Transform data
2. Visualize outliers
3. Assess which variables are the best to use.

We code together. In R or Python, I will guide you every step of the way, explaining all steps required to make an excellent regression analysis.

Did I pique your interest? I am looking forward to seeing you inside the course.

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