Certificate Programme in Survival Analysis using R

Friday, 20 February 2026 07:16:45

International applicants and their qualifications are accepted

Start Now     Viewbook

Overview

Overview

```html

Survival Analysis using R is a certificate program designed for statisticians, epidemiologists, and data scientists.


Learn statistical methods like Kaplan-Meier curves and Cox proportional hazards models.


This program utilizes the power of R for data analysis and visualization in survival analysis.


Master time-to-event data analysis and gain practical skills.


Survival Analysis techniques are essential for various fields.


Enhance your career prospects with this in-depth program.


Enroll today and become proficient in survival analysis with R. Explore the course details now!

```

Survival Analysis using R: Master this powerful statistical technique with our comprehensive certificate program. Gain practical skills in analyzing time-to-event data using R, a leading statistical software. This hands-on program covers Kaplan-Meier curves, Cox proportional hazards models, and more. Enhance your career prospects in biostatistics, epidemiology, or data science. Our unique curriculum incorporates real-world case studies and emphasizes data visualization. Boost your employability with a recognized certificate demonstrating proficiency in survival analysis and R programming.

Entry requirements

The program operates on an open enrollment basis, and there are no specific entry requirements. Individuals with a genuine interest in the subject matter are welcome to participate.

International applicants and their qualifications are accepted.

Step into a transformative journey at LSIB, where you'll become part of a vibrant community of students from over 157 nationalities.

At LSIB, we are a global family. When you join us, your qualifications are recognized and accepted, making you a valued member of our diverse, internationally connected community.

Course Content

• Introduction to Survival Analysis: Concepts and Applications
• Survival Data Structures and Descriptive Statistics in R
• Kaplan-Meier Estimation and Log-rank Test
• Parametric Survival Models: Exponential, Weibull, and Gamma
• Cox Proportional Hazards Model: Regression Techniques and Model Diagnostics
• Time-Varying Covariates in Survival Analysis
• Assessing Model Fit and Goodness-of-Fit in Survival Models
• Survival Analysis with R: Data Wrangling and Visualization using ggplot2
• Advanced Topics in Survival Analysis: Competing Risks and Frailty Models

Assessment

The evaluation process is conducted through the submission of assignments, and there are no written examinations involved.

Fee and Payment Plans

30 to 40% Cheaper than most Universities and Colleges

Duration & course fee

The programme is available in two duration modes:

1 month (Fast-track mode): 140
2 months (Standard mode): 90

Our course fee is up to 40% cheaper than most universities and colleges.

Start Now

Awarding body

The programme is awarded by London School of International Business. This program is not intended to replace or serve as an equivalent to obtaining a formal degree or diploma. It should be noted that this course is not accredited by a recognised awarding body or regulated by an authorised institution/ body.

Start Now

  • Start this course anytime from anywhere.
  • 1. Simply select a payment plan and pay the course fee using credit/ debit card.
  • 2. Course starts
  • Start Now

Got questions? Get in touch

Chat with us: Click the live chat button

+44 75 2064 7455

admissions@lsib.co.uk

+44 (0) 20 3608 0144



Career path

Career Role (Survival Analysis & R) Description
Data Scientist (Survival Analysis) Applies survival analysis techniques in R to predict customer churn, equipment failure, or other time-to-event data. High demand.
Biostatistician (Clinical Trials) Analyzes clinical trial data using survival models in R to assess treatment efficacy and safety. Strong R and statistical modelling skills needed.
Quantitative Analyst (Finance) Develops and implements survival models in R to assess credit risk, pricing derivatives, and portfolio management. Financial modelling and R programming expertise essential.
Actuary (Insurance) Utilizes R and survival analysis to model mortality rates, predict insurance claims, and manage risk. Requires strong actuarial knowledge and proficiency in R.

Key facts about Certificate Programme in Survival Analysis using R

```html

A Certificate Programme in Survival Analysis using R equips participants with the statistical skills to analyze time-to-event data. This program focuses on practical application, using the powerful statistical software R for data manipulation, model fitting, and interpretation. You will learn to handle censored data, a key characteristic of survival data analysis, and gain proficiency in various survival models.


Learning outcomes include mastering Kaplan-Meier curves for visualizing survival probabilities, understanding and applying Cox proportional hazards models—a cornerstone of survival analysis—and interpreting regression results to identify risk factors. Participants will also gain experience in model diagnostics and learn about different types of censoring mechanisms relevant to biomedical, actuarial science, and engineering applications.


The programme duration typically ranges from a few weeks to several months, depending on the intensity and delivery mode (online or in-person). The curriculum is designed for a flexible learning experience, balancing theoretical understanding with hands-on projects using real-world datasets. This practical approach ensures immediate applicability of the learned skills.


Survival analysis is highly relevant across diverse industries. In healthcare, it's crucial for clinical trials and patient prognosis; in finance, it's used for credit risk modeling and insurance pricing; and in engineering, it's essential for reliability analysis and product lifespan prediction. Completion of this Certificate Programme provides a valuable credential demonstrating expertise in this powerful statistical technique, enhancing career prospects in data science, biostatistics, and related fields.


Throughout the program, you will use R statistical software, gaining valuable experience with R packages for survival analysis, data visualization, and statistical modeling. The program also delves into advanced techniques like competing risks and frailty models, preparing you for complex survival analysis challenges.

```

Why this course?

A Certificate Programme in Survival Analysis using R is increasingly significant in today's UK market. The demand for data scientists proficient in survival analysis is growing rapidly, mirroring the broader increase in data-driven decision-making across diverse sectors. According to recent UK government statistics, the number of data science roles has increased by 35% in the last three years. This surge reflects the growing importance of analyzing time-to-event data in fields like healthcare (patient survival rates), finance (customer churn), and engineering (product lifespan). Mastering R, a powerful statistical computing language, alongside survival analysis techniques, provides a crucial competitive edge. This program equips learners with practical skills to analyze complex datasets, build predictive models, and contribute meaningfully to data-driven solutions.

Sector Growth (%)
Healthcare 40
Finance 30
Engineering 25

Who should enrol in Certificate Programme in Survival Analysis using R?

Ideal Profile Relevance
Data analysts and scientists working with time-to-event data. Gain practical skills in R programming for survival analysis, enhancing career prospects in fields like healthcare and finance.
Researchers in public health, epidemiology, and clinical trials. Develop advanced statistical modeling techniques for analyzing patient survival times and risk factors. The UK's National Health Service (NHS) relies heavily on such data analysis for resource allocation.
Actuaries and financial analysts needing to model risk and lifetimes. Master the use of Kaplan-Meier curves, Cox proportional hazards models, and other essential statistical tools for reliable risk assessments. This is crucial given the complexity of the UK's financial markets.
Postgraduate students and professionals seeking upskilling in statistical modeling. Add valuable expertise in a high-demand area; improve employability and enhance professional development.