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: Biostatistics, Statistical Analysis, R (Software), R Programming, Statistical Methods, Data Wrangling, Regression Analysis, Exploratory Data Analysis, Time Series Analysis and Forecasting, Logistic Regression, Probability & Statistics, Descriptive Statistics, Model Evaluation, Public Health
Intermediate · Course · 1 - 4 Weeks

Skills you'll gain: Time Series Analysis and Forecasting, Deep Learning, Statistical Analysis, Predictive Modeling, Statistical Methods, Forecasting, Data Preprocessing, Jupyter, Applied Machine Learning, Data Transformation, Model Evaluation, Pandas (Python Package), Unsupervised Learning, Dimensionality Reduction
Intermediate · Course · 1 - 4 Weeks

Arizona State University
Skills you'll gain: Probability & Statistics, Analytical Skills, Exploratory Data Analysis, Estimation, Logistic Regression
Intermediate · Course · 1 - 3 Months

Imperial College London
Skills you'll gain: Logistic Regression, Analytical Skills, Correlation Analysis, Regression Analysis, Sampling (Statistics), Statistical Hypothesis Testing, Data Literacy, Data Analysis, R Programming, Descriptive Statistics, Statistical Modeling, Biostatistics, Exploratory Data Analysis, Model Evaluation, Statistical Analysis, R (Software), Statistics, Statistical Methods, Data Wrangling, Public Health
Beginner · Specialization · 3 - 6 Months

Skills you'll gain: Excel Formulas, Microsoft Excel, Power BI, Spreadsheet Software, Timelines, Data Processing, Data Analysis, Data Manipulation, Data Presentation, Data Cleansing
Beginner · Course · 1 - 4 Weeks

The State University of New York
Skills you'll gain: Time Series Analysis and Forecasting, Forecasting, R Programming, Statistical Analysis, Model Evaluation, Data Analysis, Data Visualization, Mathematical Modeling, Statistical Modeling, Correlation Analysis, Probability & Statistics, Descriptive Statistics, Statistical Inference, Software Installation
Intermediate · Course · 1 - 3 Months
University of Illinois Urbana-Champaign
Skills you'll gain: Financial Statements, Financial Statement Analysis, Financial Forecasting, Financial Accounting, Variance Analysis, Financial Analysis, Income Statement, Balance Sheet, Performance Measurement, Management Accounting, Return On Investment, Revenue Forecasting, Financial Management, Profit and Loss (P&L) Management, Cost Management, Financial Data, Budgeting, Finance, Accounting, Cash Flows
Beginner · Specialization · 1 - 3 Months

University of Colorado Boulder
Skills you'll gain: Unsupervised Learning, Regression Analysis, Classification Algorithms, Dimensionality Reduction, Data Analysis, Anomaly Detection, Supervised Learning, Model Evaluation, Statistical Analysis, Analytics, Logistic Regression, Data Preprocessing, Predictive Modeling, Applied Machine Learning, Statistical Modeling, Machine Learning Methods, Data Mining, Machine Learning Algorithms, Exploratory Data Analysis, Machine Learning
Intermediate · Specialization · 3 - 6 Months
Rice University
Skills you'll gain: Statistical Hypothesis Testing, Microsoft Excel, Statistical Methods, Pivot Tables And Charts, Regression Analysis, Statistics, Descriptive Statistics, Probability & Statistics, Graphing, Spreadsheet Software, Probability Distribution, Business Analytics, Statistical Modeling, Statistical Analysis, Statistical Inference, Excel Formulas, Data Analysis, Data Presentation, Model Evaluation, Sample Size Determination
Beginner · Specialization · 3 - 6 Months

Macquarie University
Skills you'll gain: Pivot Tables And Charts, Sample Size Determination, Data Visualization, Statistical Inference, Data Visualization Software, Statistical Hypothesis Testing, Statistics, Data-Driven Decision-Making, Microsoft Excel, Correlation Analysis, Descriptive Statistics, Probability & Statistics, Data Analysis, Forecasting, Regression Analysis, Business Analytics, Spreadsheet Software, Statistical Modeling, Statistical Visualization, Data Presentation
Beginner · Specialization · 3 - 6 Months
University of Michigan
Skills you'll gain: R (Software), Model Evaluation, Statistical Modeling, Statistics, Data Visualization, Data Wrangling, Data Manipulation, Correlation Analysis, Histogram, Data Analysis, Statistical Analysis, Biostatistics, Statistical Hypothesis Testing, Scripting, Package and Software Management, Data Import/Export
Beginner · Specialization · 1 - 3 Months

Skills you'll gain: Logistic Regression, SAS (Software), Predictive Modeling, Model Evaluation, Predictive Analytics, Statistical Hypothesis Testing, Statistical Analysis, Correlation Analysis, Statistical Modeling, Regression Analysis, Statistical Methods, Probability & Statistics, Classification And Regression Tree (CART), Big Data, Plot (Graphics), Data Analysis, Model Deployment, Statistical Inference, Statistical Machine Learning, Feature Engineering
Intermediate · Professional Certificate · 3 - 6 Months
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.