Survival analysis courses can help you learn techniques for estimating life expectancy, analyzing time-to-event data, and understanding hazard functions. You can build skills in censoring techniques, Kaplan-Meier estimators, and Cox proportional hazards modeling. Many courses introduce tools like R and Python for statistical computing, along with software for visualizing survival curves and interpreting results in various contexts, such as healthcare and engineering.

Imperial College London
Skills you'll gain: Statistical Analysis, R (Software), R Programming, Data Wrangling, Regression Analysis, Exploratory Data Analysis, Data Analysis, Logistic Regression, Probability & Statistics, Statistical Modeling, Statistical Hypothesis Testing, Descriptive Statistics, Model Evaluation, Public Health
★ 4.5 (331) · Intermediate · Course · 1 - 4 Weeks

Skills you'll gain: Time Series Analysis and Forecasting, Deep Learning, Statistical Analysis, Forecasting, Statistical Machine Learning, Data Cleansing, Data Transformation, Unsupervised Learning, Dimensionality Reduction
★ 4.5 (147) · Intermediate · Course · 1 - 4 Weeks

Imperial College London
Skills you'll gain: Logistic Regression, Correlation Analysis, Regression Analysis, Sampling (Statistics), Statistical Hypothesis Testing, Statistical Analysis, R (Software), Data Analysis, R Programming, Descriptive Statistics, Statistical Software, Statistical Modeling, Model Evaluation, Probability & Statistics, Statistical Methods, Data Analysis Software, Data Wrangling, Statistics, Public Health, Statistical Inference
★ 4.7 (2.1K) · Beginner · Specialization · 3 - 6 Months
Skills you'll gain: Regression Analysis, Statistical Hypothesis Testing, Logistic Regression, Statistical Analysis, Data Analysis, Statistical Methods, Correlation Analysis, Predictive Modeling, Statistical Modeling, Machine Learning, Model Evaluation, Variance Analysis, Python Programming
★ 4.7 (612) · Advanced · Course · 1 - 3 Months

The State University of New York
Skills you'll gain: Time Series Analysis and Forecasting, R (Software), Forecasting, R Programming, Statistical Analysis, Model Evaluation, Data Analysis, Statistical Visualization, Mathematical Modeling, Statistical Modeling, Correlation Analysis, Descriptive Statistics, Statistical Inference
★ 4.6 (1.7K) · Intermediate · Course · 1 - 3 Months

University of Colorado Boulder
Skills you'll gain: Regression Analysis, Statistical Methods, Correlation Analysis, Statistical Hypothesis Testing, Statistical Inference, Statistical Modeling, Statistical Analysis, Probability & Statistics, Statistics, Predictive Modeling, Analysis, Scatter Plots, Model Evaluation, Estimation, Sampling (Statistics)
Mixed · Course · 1 - 3 Months

Johns Hopkins University
Skills you'll gain: Biostatistics, Regression Analysis, Logistic Regression, Statistical Methods, Public Health, Probability & Statistics, Statistical Analysis, Statistical Inference, Statistical Modeling, Predictive Modeling, Data Analysis
★ 4.8 (333) · Beginner · Course · 1 - 4 Weeks
Rice University
Skills you'll gain: Statistical Hypothesis Testing, Microsoft Excel, Pivot Tables And Charts, Regression Analysis, Statistics, Descriptive Statistics, Probability & Statistics, Graphing, Spreadsheet Software, Probability Distribution, Statistical Analysis, Statistical Modeling, Statistical Inference, Excel Formulas, Business Analytics, Data Analysis, Data Presentation, Model Evaluation, Statistical Methods, Sample Size Determination
★ 4.7 (13K) · Beginner · Specialization · 3 - 6 Months

Sage Publications
Skills you'll gain: Time Series Analysis and Forecasting, Stata, Logistic Regression, STATA (Software), Quantitative Research, Regression Analysis, Descriptive Statistics, Forecasting, Exploratory Data Analysis, Data Entry, Statistical Inference, Statistical Methods, Probability & Statistics, Statistical Analysis, Statistical Modeling, Statistical Programming, Data Import/Export, Data Transformation, Statistical Reporting, Data Analysis
Intermediate · Specialization · 3 - 6 Months

Macquarie University
Skills you'll gain: Data Visualization, Statistical Inference, Statistical Hypothesis Testing, Data-Driven Decision-Making, Descriptive Statistics, Statistical Analysis, Statistical Methods, Sampling (Statistics), Excel Formulas, Spreadsheet Software, Box Plots, Time Series Analysis and Forecasting, Data Analysis Software, Statistical Modeling, Advanced Analytics, Financial Forecasting, Probability Distribution, Descriptive Analytics, Variance Analysis, Predictive Modeling
★ 4.6 (145) · Beginner · Specialization · 3 - 6 Months

Skills you'll gain: Root Cause Analysis, Operational Efficiency, Continuous Improvement Process, Quality Improvement, Product Quality (QA/QC), Process Improvement, Operational Excellence, Critical Thinking and Problem Solving, Complex Problem Solving, Critical Thinking
★ 4.5 (119) · Beginner · Course · 1 - 4 Weeks

Skills you'll gain: SQL Server Reporting Services, Data Visualization, Dashboard, Dashboard Creation, Interactive Data Visualization, Data Presentation, Microsoft Excel, Excel Macros, Data Visualization Software, Excel Formulas, Microsoft SQL Servers, Business Reporting, Business Intelligence, SQL, Data Analysis, Analytics, Automation, Analysis, Business, Design
★ 4.7 (17) · Beginner · Specialization · 1 - 3 Months
Top-rated Survival Analysis courses offered by Imperial College London on Coursera.
Earn a certificate in Survival Analysis from top universities and companies.
Top-rated beginner-friendly Survival Analysis courses with no prerequisites.
Survival analysis is a statistical approach used to analyze the time until an event occurs, such as death, failure, or any other significant event. It is crucial in various fields, including healthcare, engineering, and social sciences, as it helps researchers and practitioners understand the factors influencing the timing of events. By estimating survival functions and hazard rates, survival analysis provides insights that can inform decision-making and improve outcomes.
Careers in survival analysis span multiple industries. Common job titles include biostatistician, data analyst, clinical researcher, and epidemiologist. Professionals in these roles often work with healthcare organizations, pharmaceutical companies, and research institutions, applying survival analysis techniques to study patient outcomes, treatment effectiveness, and risk factors. The demand for skilled analysts in this area continues to grow, making it a promising career path.
To excel in survival analysis, you should develop a strong foundation in statistics, particularly in concepts like probability distributions, regression models, and hypothesis testing. Proficiency in statistical software, such as R or Python, is essential for data manipulation and analysis. Additionally, understanding the context of your data—whether in healthcare, engineering, or social sciences—will enhance your ability to apply survival analysis effectively.
Some of the best online courses for survival analysis include Survival Analysis in R for Public Health and Specialized Models: Time Series and Survival Analysis. These courses provide practical skills and theoretical knowledge, allowing learners to apply survival analysis techniques in real-world scenarios.
Yes. You can start learning survival analysis on Coursera for free in two ways:
If you want to keep learning, earn a certificate in survival analysis, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.
To learn survival analysis, start by enrolling in online courses that cover the fundamentals and applications of the topic. Engage with practical exercises and real-world datasets to reinforce your understanding. Additionally, consider joining online forums or study groups to discuss concepts and share insights with peers. Regular practice and application of techniques will enhance your skills over time.
Typical topics covered in survival analysis courses include survival functions, hazard functions, Kaplan-Meier estimators, Cox proportional hazards models, and competing risks. Courses may also explore the application of these concepts in various fields, such as healthcare and engineering, providing a comprehensive understanding of how to analyze time-to-event data.
For training and upskilling employees in survival analysis, consider courses like Survival Analysis in R for Public Health and Specialized Models: Time Series and Survival Analysis. These courses are designed to equip professionals with the necessary skills to apply survival analysis techniques effectively in their work environments.