AIMS OF THE COURSE

Are you ready to explore the world of time-to-event data, particularly survival analysis and master the essential techniques used in medical research, public health, and social sciences? This course is designed to equip you with both the theoretical understanding and practical skills needed to confidently perform survival analysis using R.

WHO THIS COURSE IS FOR?

Whether you're a student, researcher, or data professional, this course will walk you through key survival analysis concepts—from censoring and survival functions to advanced models like the Cox 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 as censoring, hazard functions, and survival curves.

• Understand the fundamentals of survival analysis methods including Kaplan-Meier analysis, Log-rank test, and Cox regression.

• Proficiently perform survival analyses as well as build Cox regression model using R

• 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 Nguyen is a dedicated educator and experienced data analysis with a strong background in biotechnology, biology, and statistical analysis and modeling. He holds a PhD and MSc from Flinders University, with additional qualifications from Mahidol University, Osaka University, and Hanoi University of Science (VNU). Lam has served as a lecturer, research associate, and consultant, working across academic and applied research projects in Australia and Asia.

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