Udemy course Regression Analysis for Business Managers in Python and R by Diogo Alves de Resende
Regression Analysis for Business Managers in Python and R is the best Udemy course on the market. With this offer they will be able to greatly improve their knowledge and become more competitive within the Business category. Therefore, if you are looking to improve your Business skills we recommend that you download Regression Analysis for Business Managers in Python and R udemy course.
Here you can see Udemy courses linked to: Business.
Course data:
- Author: Diogo Alves de Resende
- Course rating: 4.6
- Category: Business
- Modality: Online
- Status: Available
- Idiom: English
Abouth Diogo Alves de Resende
Hey guys! I am thrilled that you are reading this. I work for one of the biggest e-commerce companies, focused on business analytics, and it is the methodologies I have used in my job that I want to teach.
What the udemy Regression Analysis for Business Managers in Python and R course teaches?
What you’ll learn Linear Regression Logistic Regression Pricing Churn drivers Data Manipulation R and Python
Learn how to use Linear & Logistic Regressions by solving 2 Business Case studies in Python & R. Code templates included
More information about the course Regression Analysis for Business Managers in Python and R
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: Transform data Visualize outliers 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.
