Why this course?

Description

Are you tired of reading and going through technical, jargon-filled content of different modeling techniques? If yes, don't worry. We are there to help you. 

This course on logistic regression provides a 360 degree coverage of the topic using easy to understand language, conceptual and practical questions and case study to provide hands-on practice. 

Logistic Regression is one of the most prominent and preferred predictive modeling technique used worldwide. Logistic regression finds its application in almost all the industries - retail, banking, e-commerce, healthcare, manufacturing. Logistic regression model is a simple yet very powerful modeling technique.

Comprehensive Coverage

This course is meant to provide students and professsionals an indepth knowledge of logistic regression. This course is meant to add value and increase knowledge base of all analytics professionals from beginner to advanced level. This course can prepare any professional for any analtyics-related job interview with its exhaustive coverage of 80+ questions (and counting) focusing on logistic regression.

Through its extensive coverage, this course builds theoretical knowledge for a student, test her knowledge through best-in-class questions and provides insights to industry application through case studies.

Who should opt for this course?

• Anyone who wishes to develop theoretical and practical understanding of logistic regression
• Any student or professional preparing for job interview and wish to learn logistic regression
• Any professional willing to implement logistic regression at her work
• Any student willing to work on academic projects using logistic regression

Course Coverage

This course covers logistic regression in great depth and covers following aspects:

• Basics of logistic regression
• Type of logistic regression
• Mathematics underlying the logistic regression
• Assumptions of logistic regression
• Odds ratio and the relevance of odds ratio for logistic regression
• Different output measures for logistic regression
• Building a logistic regression in Python
• Applications of logistic regression in industry
• Case study to implement and understand the relevance of logistic regression
• 80+ (and counting) conceptual and practical question to test your understanding
• 5 practice test to help you develop detailed understanding of the concept
• 1 Evaluation test to test your knowledge

In case of any query, please reach out to us at info@aimonks.com.