Overview
Context
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.
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 Survival Analysis in Python course at Data Camp, you’ll be able to model survival distributions, build pretty plots of survival curves, and even predict survival durations.
Programme Structure
Chapters
- Survival Curve Estimation
- The Weibull Model
- The Cox PH Model
Key information
Duration
- Part-time
- 1 days
Start dates & application deadlines
You can apply for and start this programme anytime.
Language
English
Delivered
Online
Disciplines
Software Engineering View 554 other Short Courses in Software Engineering in United StatesAcademic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
PREREQUISITES
- Introduction to Regression with statsmodels in Python
- Statistical Thinking in Python (Part 2)
Tuition Fee
To always see correct tuition fees
-
International
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 days. -
National
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 days.
Basic Access: Free; Premium (for individuals): $12.42 per month billed annually; Teams: $25 per month billed annually; Enterprise: Contact sales for pricing
Funding
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