The Complete Survival Analysis Course in R

https://www.udemy.com/course/the-complete-survival-analysis-course-in-r
A complete course of Survival Analysis from basic concepts to real life projects

What you'll learn
- Understand core concepts in survival analysis (e.g, censoring, survival function, hazard function).
- Understand the fundamentals of survival analysis methods (e.g., Kaplan-Meier analysis, Log-rank test, Cox regression).
- Proficiently perform survival analyses as well as build Cox regression model using R.
- Check the assumptions for survival analyses and handle violations.

Requirements
- No prior experience in survival analysis is required, but a basic understanding of R and statistics will help you get the most from the course.

Description
AIMS OF THE COURSE

Are you ready to explore the world oftime-to-event data, particularly survival analysisand master the essential techniques used in medical research, public health, and social sciences? This course is designed to equip you with both thetheoretical understandingandpractical skillsneeded to confidently perform survival analysis usingR.

WHO THIS COURSE IS FOR?

Whether you're a student, researcher, or data professional, this course will walk you through key survival analysis concepts—fromcensoring and survival functionsto advanced models like theCox proportional hazards regression. You’ll not only learn the theory but also apply it to real-world projects and datasets.

OUTCOMES

By the end of the course, you will be able to:

Grasp core concepts in survival analysis such ascensoring,hazard functions, andsurvival curves.

Understand the fundamentals of survival analysis methods includingKaplan-Meier analysis,Log-rank test, andCox regression.

Proficiently performsurvival analysesas well as buildCox regression modelusingR

Create summary tables and charts (i.e., KM curve, baseline hazards  and hazards rates)

Evaluate and test model assumptions, and handle violations.

ABOUT MYSELF

Lam Nguyenis a dedicated educator and experienced data analysis with a strong background inbiotechnology, biology, and statistical analysis and modeling. He holds aPhD and MScfromFlinders University, with additional qualifications fromMahidol University,Osaka University, andHanoi University of Science (VNU). Lam has served as alecturer,research associate, andconsultant, working across academic and applied research projects in Australia and Asia.

With a passion forcoding, data analysis, and lifelong learning, Lam brings both academic rigor and hands-on insight to this course, ensuring learners gain practical, applicable skills.

Who this course is for:
- Graduate students in biostatistics, epidemiology and public health
- Researchers working with time-to-event data
- Data scientists and analysts in healthcare and other fields
More Info