Datacamp – Survival Analysis in Python 2023-11

Survival Analysis in Python, How long does it take for flu symptoms to show after exposure? And what if you don’t know when people caught the virus? Do salary and work-life balance influence the speed of employee turnover? Lots of real-life challenges require survival analysis to robustly estimate the time until an event to help us draw insights from time-to-event distributions. This course introduces you to the basic concepts of survival analysis. Through hands-on practice, you’ll learn how to compute, visualize, interpret, and compare survival curves using Kaplan-Meier, Weibull, and Cox PH models. By the end of this course, you’ll be able to model survival distributions, build pretty plots of survival curves, and even predict survival durations.

What you’ll learn

• Introduction to Survival Analysis
• Survival Curve Estimation
• The Weibull Model
• The Cox PH Model

Specificatoin of Survival Analysis in Python

• Publisher : Datacamp
• Teacher : Shae Wang
• Language : English
• Level : All Levels
• Number of Course : 4
• Duration : 4 hours to complete the course

Content of Survival Analysis in Python

Requirements

• Introduction to Regression with statsmodels in Python
• Hypothesis Testing in Python

Pictures

Sample Clip

Installation Guide

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Quality: 720p

Download Links

Download – 90 MB

File size

90 MB