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Survival Analysis Courses

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.

Popular Survival Analysis Courses and Certifications


  • I

    Imperial College London

    Survival Analysis in R for Public Health

    Skills you'll gain: Biostatistics, Statistical Analysis, R (Software), R Programming, Statistical Methods, Data Wrangling, Regression Analysis, Exploratory Data Analysis, Statistical Software, Data Analysis, Logistic Regression, Probability & Statistics, Statistical Modeling, Descriptive Statistics, Model Evaluation, Public Health

    ★ 4.5 (331) · Intermediate · Course · 1 - 4 Weeks

    Status: Free Trial
    Free Trial
  • I

    IBM

    Specialized Models: Time Series and Survival Analysis

    Skills you'll gain: Time Series Analysis and Forecasting, Deep Learning, Statistical Analysis, Predictive Modeling, Statistical Methods, Forecasting, Data Preprocessing, Statistical Modeling, Statistical Machine Learning, Applied Machine Learning, Data Transformation, Model Evaluation, Unsupervised Learning, Dimensionality Reduction

    ★ 4.5 (147) · Intermediate · Course · 1 - 4 Weeks

  • I

    Imperial College London

    Statistical Analysis with R for Public Health

    Skills you'll gain: Logistic Regression, Analytical Skills, Correlation Analysis, Science and Research, Regression Analysis, Sampling (Statistics), Statistical Hypothesis Testing, Data Literacy, Data Analysis, R Programming, Descriptive Analytics, Descriptive Statistics, Statistical Software, Statistical Modeling, Biostatistics, Model Evaluation, Exploratory Data Analysis, Statistical Analysis, Statistical Programming, R (Software)

    ★ 4.7 (2.1K) · Beginner · Specialization · 3 - 6 Months

    Status: Free Trial
    Free Trial
  • G

    Google

    Regression Analysis: Simplify Complex Data Relationships

    Skills you'll gain: Regression Analysis, Statistical Hypothesis Testing, Logistic Regression, Statistical Analysis, Data Analysis, Statistical Methods, Correlation Analysis, Predictive Modeling, Supervised Learning, Predictive Analytics, Statistical Modeling, Machine Learning, Model Evaluation, Applied Machine Learning, Variance Analysis, Classification Algorithms, Python Programming

    ★ 4.7 (605) · Advanced · Course · 1 - 3 Months

    Status: Free Trial
    Free Trial
  • T

    The State University of New York

    Practical Time Series Analysis

    Skills you'll gain: Time Series Analysis and Forecasting, R (Software), Forecasting, R Programming, Statistical Analysis, Model Evaluation, Data Analysis, Statistical Programming, Data Visualization, Statistical Visualization, Statistical Software, Mathematical Modeling, Statistical Methods, Statistical Modeling, Predictive Analytics, Predictive Modeling, Correlation Analysis, Descriptive Statistics, Statistical Inference, Data Transformation

    ★ 4.6 (1.7K) · Intermediate · Course · 1 - 3 Months

    Category: Preview
    Preview
  • J

    Johns Hopkins University

    Multiple Regression Analysis in Public Health

    Skills you'll gain: Biostatistics, Regression Analysis, Logistic Regression, Statistical Methods, Public Health, Statistical Analysis, Statistical Inference, Statistical Modeling, Predictive Modeling, Quantitative Research, Data Analysis, Statistical Hypothesis Testing, Model Evaluation

    ★ 4.8 (331) · Beginner · Course · 1 - 4 Weeks

    Status: Free Trial
    Free Trial

What brings you to Coursera today?

  • U

    University of Michigan

    Logistic Regression and Prediction for Health Data

    Skills you'll gain: Logistic Regression, Model Evaluation, Statistical Inference, Predictive Analytics, R Programming, Predictive Modeling, Probability & Statistics, Statistical Modeling, Statistical Methods, Biostatistics, Regression Analysis, Statistical Analysis, Statistical Hypothesis Testing, Data Analysis, Epidemiology, Descriptive Statistics

    Intermediate · Course · 1 - 4 Weeks

    Status: Free Trial
    Free Trial
  • IBM Logo

    Explore what's possible with IBM

    Enroll today
  • M

    Microsoft

    Preparing Data for Analysis with Microsoft Excel

    Skills you'll gain: Microsoft Excel, Excel Formulas, Spreadsheet Software, Power BI, Data Analysis, Timelines, Data Management, Data Entry, Data Presentation

    ★ 4.7 (5.7K) · Beginner · Course · 1 - 4 Weeks

    Status: Free Trial
    Free Trial
  • A

    Arizona State University

    Probability, Statistical Inference and Regression Analysis

    Skills you'll gain: Statistics, Probability & Statistics, Analytics, Exploratory Data Analysis, Estimation, Logistic Regression

    Intermediate · Course · 1 - 3 Months

    Status: Free Trial
    Free Trial
  • C

    Coursera

    Analyze Healthcare Data with Confidence

    Skills you'll gain: Statistical Inference, Statistical Analysis, Data Literacy, Data Analysis, Probability & Statistics, Estimation, Correlation Analysis

    Beginner · Course · 1 - 4 Weeks

    Category: New
    New
    Status: Free Trial
    Free Trial
  • C

    Coursera

    Perform Cohort Analysis

    Skills you'll gain: Customer Retention, Customer Analysis, Brand Loyalty, Conversion Funnel Analysis, Customer Insights, Web Analytics, Google Analytics, Customer Success Management, Customer Engagement, Customer Acquisition Management, Trend Analysis, Marketing Effectiveness, Customer experience improvement, Business Metrics, Analysis, Performance Metric, Target Audience

    Beginner · Course · 1 - 4 Weeks

    Category: New
    New
    Status: Free Trial
    Free Trial
  • U

    University of Illinois Urbana-Champaign

    Financial Analysis - Skills for Success

    Skills you'll gain: Financial Statements, Financial Statement Analysis, Financial Forecasting, Budget Management, Variance Analysis, Financial Analysis, Income Statement, Balance Sheet, Performance Measurement, Forecasting, Management Accounting, Return On Investment, Financial Data, Cash Flow Forecasting, Cost Management, Budgeting, Financial Modeling, Finance, Accounting, Financial Accounting

    ★ 4.7 (533) · Beginner · Specialization · 1 - 3 Months

    Status: Free Trial
    Free Trial

What brings you to Coursera today?

1234…834

In summary, here are 10 of our most popular survival analysis courses

  • Survival Analysis in R for Public Health: Imperial College London
  • Specialized Models: Time Series and Survival Analysis: IBM
  • Statistical Analysis with R for Public Health: Imperial College London
  • Regression Analysis: Simplify Complex Data Relationships: Google
  • Practical Time Series Analysis: The State University of New York
  • Multiple Regression Analysis in Public Health: Johns Hopkins University
  • Logistic Regression and Prediction for Health Data: University of Michigan
  • Preparing Data for Analysis with Microsoft Excel: Microsoft
  • Probability, Statistical Inference and Regression Analysis: Arizona State University
  • Analyze Healthcare Data with Confidence: Coursera

Frequently Asked Questions about Survival Analysis

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‚Äîwhether in healthcare, engineering, or social sciences‚Äîwill 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:

  1. Preview the first module of many survival analysis courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

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.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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