Description
Survival Analysis in Python, training course Survival Analysis in Python is published by Datacamp Academy. How long does it take for flu symptoms to appear after exposure? And what if you don’t know when people got the virus? Does salary and work-life balance affect the speed of employee turnover? Many real-life challenges require survival analysis to accurately estimate the time to a given event, which helps us to obtain information from time-to-event distributions. This course introduces you to the basic concepts of survival analysis. Through hands-on practice, you will learn how to calculate, visualize, interpret, and compare survival curves using Kaplan-Meier, Weibull, and Cox PH models. By the end of this course, you will be able to model survival distributions, construct beautiful plots of survival curves, and even predict survival times.
What you will learn
- An introduction to survival analysis
- Estimation of the survival curve
- Weibull model
- Cox PH model
Survival Analysis in Python course specifications
- Publisher: Datacamp
- teacher : Shae Wang
- English language
- Education level: all levels
- Number of courses: 4
- Training duration: 4 hours to complete the course
Chapters of Survival Analysis in Python course
Course prerequisites
- Introduction to Regression with statistical models in Python
- Hypothesis Testing in Python
Pictures
Sample video
Installation guide
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download link
File(s) password: www.downloadly.ir
Size
90 MB
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