Cesar’s course is rated: Excellent
Rated 4.6 out of 5
4.8 out of 5 based on over 2.5k+ reviews
DATA ANALYSIS COURSE USING R
In-person training
Master data analysis with CESAR’s comprehensive R. Learn to manipulate data, create stunning visualizations, and run advanced statistical tests all using the world’s most powerful statistical software.
R13 500.00 Excluding VAT
DATA ANALYSIS COURSE USING R
In-person training
Master data analysis with CESAR’s comprehensive R Course. Learn to manipulate data, create stunning visualizations, and run advanced statistical tests, all using the world’s most powerful statistical software.
R13 500.00 Excluding VAT
3.8k+
Cesar’s course is rated: Excellent
Rated 4.6 out of 5
4.8 out of 5 based on over 3.8k+ reviews
Course Overview:
R is a programming language and free software environment for statistical computing and beautiful data visualisation. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, etc.) and graphical techniques. Being a full programming language, R is highly extensible.
R is now widely regarded as the best software for statistical analysis and data science. It is a fast, powerful statistical package designed by statisticians for data analysts of all disciplines. With Base R and a library of packages, the analyst has everything for data management, analysis, and data visualisation. One of R’s strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed.
In this course, participants will experience the desired qualities and functionalities that make R widely preferred. R is absolutely free. It compiles and runs on a wide variety of UNIX platforms, Windows, and macOS. Our facilitators are experienced, intentional, interactive, and friendly. We invite you to join this course and take your data analysis and visualisation skills to the next level.
LIMITED OFFER VALID UNTIL 18TH MARCH 2026.
- Training Schedule
- Status
- Training Format
- Training Cost
- 23–27 March 2026
- Accepting Enrollments
- In person training
- R13 500.00 Excluding VAT
We’ve taken care of every detail so you can focus entirely on learning. Your registration includes:
- Course attendance
- Full 5-day course attendance
- All refreshments: Welcome tea, two tea breaks (tea and pastries), and a full lunch daily
- Comprehensive lecture notes and training manual
- Complimentary and secure parking
- Certificate of attendance upon completion
SECURE YOUR SPOT BEFORE TIME RUNS OUT:
Days
Hours
Minutes
Seconds
Dates
23–27 March 2026
Status
Accepting Applications
Training Format
In-Person Training
5 Days In-Person Training
R13 500.00 Excluding VAT
LIMITED OFFER VALID UNTIL 18TH MARCH 2026.
Days
Hours
Minutes
Seconds
Course Overview
R is a programming language and free software environment for statistical computing and beautiful data visualisation. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, etc.) and graphical techniques. Being a full programming language, R is highly extensible.
R is now widely regarded as the best software for statistical analysis and data science. It is a fast, powerful statistical package designed by statisticians for data analysts of all disciplines. With Base R and a library of packages, the analyst has everything for data management, analysis, and data visualisation. One of R’s strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed.
In this course, participants will experience the desired qualities and functionalities that make R widely preferred. R is absolutely free. It compiles and runs on a wide variety of UNIX platforms, Windows, and macOS. Our facilitators are experienced, intentional, interactive, and friendly. We invite you to join this course and take your data analysis and visualisation skills to the next level.
Registration Inclusions
We’ve taken care of every detail so you can focus entirely on learning. Your registration includes:
- Full 5-day course attendance
- All refreshments: Welcome tea, two tea breaks (tea and pastries), and a full lunch daily
- Comprehensive lecture notes and training manual
- Complimentary and secure parking
- Certificate of attendance upon completion
⚡ Course Objectives
What You Will Achieve
The course uses a fine blend of interactive discussions, group exercises, self-paced learning, and practical project reports to simulate real-world applications. By the end of the course, participants will be able to:
01. MASTER THE R ENVIRONMENT
Navigate Base R and RStudio with confidence, understand the R workspace and working directories, and write efficient, reproducible scripts using R scripts and R Markdown. Learn to manage packages, objects, and project files systematically to track and organise your work. Stop repeating manual tasks and start building clean, automated, and reproducible workflows in R.
02. MANAGE & CLEAN DATA LIKE A PRO
Import data from Excel, CSV, and other formats into R with confidence. Learn how to structure, append and merge datasets from multiple sources while preserving data integrity. Master the essential process of data cleaning to ensure your analyses are accurate and reproducible.
Learn the popular tidyverse ecosystem, including packages such as dplyr and tidyr, for efficient data cleaning and management in R.
03. Perform Real-World Data Analysis Projects
Move beyond basic summaries. Conduct normality tests, describe data succinctly and accurately. Perform subgroup (stratified) analyses with confidence. Learn ggplot2 to create best-in-class data visualisations—elegant, publication-quality, fully customisable graphs that communicate insights clearly and powerfully.
04. MASTER INFERENTIAL STATISTICS
Demystify statistical jargon. Gain a clear understanding of p-values, confidence intervals, and hypothesis testing. Learn to conduct and interpret key tests including Chi-squared and Fisher’s exact tests, as well as parametric and non-parametric methods (t-tests, Wilcoxon rank-sum, Kruskal–Wallis).
05. WRITE & APPRAISE RESEARCH PUBLICATIONS
Develop the skills to write clear, statistically sound research reports and critically evaluate academic papers. Understand the methods applied, assess the validity of findings, and communicate results with clarity and confidence.
Course Curriculum at a Glance
| Day 1Introduction to data and R Software | Day 2Data Management using R | Day 3Descriptive statistics and Subgroup analysis | Day 4Confidence intervals and chi squared test | Day 5Parametric and non parametric tests |
|---|---|---|---|---|
| Research Questions & Data Structure Research questions · Data structure | R Script Files Organising and running R code | Making Sense of Data Concepts in descriptive statistics | Confidence Intervals Calculating and interpreting confidence intervals | Parametric & Non-Parametric Tests t-test · ANOVA · Rank-sum · Kruskal-Wallis · Correlation |
| Introduction to R Exploring R · Comparing with Stata & Python · Downloading R & RStudio | Reading & Importing Data Reading and importing data into R | Descriptive Analysis in R Using R for descriptive and subgroup analysis | Statistical Tests Different types of statistical tests · The chi-square test | Measures of Effect Measures of effect · Introduction to multiple regression |
| Working in R Data structures · Functions · Accessing packages · Writing functions | Basic Data Management Basic data management procedures in R | Data Visualisation Data visualisation using R | — | Final Project Report |
| R Programming Rules R programming rules and best practices | — | |||
Day 1
Introduction to data and R Software
Research Questions & Data Structure
Research questions · Data structure
Introduction to R
Exploring R · Comparing with Stata & Python · Downloading R & RStudio
Lunch break
Working in R
Data structures · Functions · Accessing packages · Writing functions
R Programming Rules
R programming rules and best practices
Day 2
Data Management using R
R Script Files
Organising and running R code
Reading & Importing Data
Reading and importing data into R
Lunch break
Basic Data Management
Basic data management procedures in R
Day 3
Descriptive statistics and Subgroup analysis
Making Sense of Data
Concepts in descriptive statistics
Descriptive Analysis in R
Using R for descriptive and subgroup analysis
Lunch break
Data Visualisation
Data visualisation using R
Day 4
Confidence intervals and chi squared test
Confidence Intervals
Calculating and interpreting confidence intervals
Statistical Tests
Different types of statistical tests · The chi-square test
Day 5
Parametric and non parametric tests
Parametric & Non-Parametric Tests
t-test · ANOVA · Rank-sum · Kruskal-Wallis · Correlation
Measures of Effect
Measures of effect · Introduction to multiple regression
Lunch break
Final Project Report
| Week 1Introduction to data and R Software | Week 2Data Management using R | Week 3Descriptive statistics and Subgroup analysis | Week 4Inferential Statistics |
|---|---|---|---|
| Research Questions & Data Structure Research questions · Data structure | R Script Files Organising and running R code | Making Sense of Data Concepts in descriptive statistics | Confidence Intervals Calculating and interpreting confidence intervals |
| Introduction to R Exploring R · Comparing with Stata & Python · Downloading R & RStudio | Reading & Importing Data Reading and importing data into R | Descriptive & Subgroup Analysis Using R for descriptive analysis · Using R for subgroup analysis | Statistical Tests Different types of statistical tests · The chi-square test |
| Working in R Data structures · Functions · Accessing packages · Writing R functions | Basic Data Management Basic data management procedures in R | Data Visualisation Data visualisation using R | Parametric & Non-Parametric Tests t-test · ANOVA · Rank-sum · Kruskal-Wallis · Correlation |
| R Programming Rules R programming rules and best practices | Measures of Effect & Multiple Regression Measures of effect · Introduction to multiple regression | ||
Week 1
Introduction to data and R Software
Research Questions & Data Structure
Research questions · Data structure
Introduction to R
Exploring R · Comparing with Stata & Python · Downloading R & RStudio
Working in R
Data structures · Functions · Accessing packages · Writing R functions
R Programming Rules
R programming rules and best practices
Week 2
Data Management using R
R Script Files
Organising and running R code
Reading & Importing Data
Reading and importing data into R
Basic Data Management
Basic data management procedures in R
Week 3
Descriptive statistics and Subgroup analysis
Making Sense of Data
Concepts in descriptive statistics
Descriptive & Subgroup Analysis
Using R for descriptive analysis · Using R for subgroup analysis
Data Visualisation
Data visualisation using R
Week 4
Inferential Statistics
Confidence Intervals
Calculating and interpreting confidence intervals
Statistical Tests
Different types of statistical tests · The chi-square test
Parametric & Non-Parametric Tests
t-test · ANOVA · Rank-sum · Kruskal-Wallis · Correlation
Measures of Effect & Multiple Regression
Measures of effect · Introduction to multiple regression
Why learn R with CESAR
CESAR is a world-class training and consultancy organization based in Johannesburg, South Africa. Since our founding, we’ve trained professionals from 35 countries across four continents. Over time, we’ve grown into one of the continent’s most trusted providers of statistical training. We don’t just teach, we work with organizations to support better decisions through data.
Our Approach Prioritizes:
Hands-on Learning
Work through realistic datasets and guided projects that build confidence step by step, so you don’t just watch tutorials, you actively practice how Stata is used in real analysis.
Current Knowledge
Learn modern methods used by leading global health and research bodies like the World Health Organization, UNAIDS, and The Global Fund, not outdated textbook examples.
Real-World Application
Train with field-based scenarios that reflect the decisions analysts face daily, helping you interpret results clearly and apply Stata insights to actual research and reports.
Why Learn R with CESAR?
CESAR is a world-class training and consultancy organization based in Johannesburg, South Africa. Since our founding, we’ve trained professionals from 35 countries across four continents. Over time, we’ve grown into one of the continent’s most trusted providers of statistical training. We don’t just teach, we work with organizations to support better decisions through data. Our approach prioritizes:
– Hands-on Learning: This isn’t a passive lecture. You’ll work through real datasets and guided projects that build your confidence step-by-step. You won’t just watch tutorials; you’ll actively practice how R is used in real analysis, from data cleaning to final output.
– Current Knowledge: Learn the modern methods used by leading global health and research bodies like the World Health Organization, UNAIDS, and The Global Fund. We focus on the techniques and packages used by today’s professionals, moving beyond outdated textbook examples.
– Real-World Application: This training is grounded in field-based scenarios that reflect the decisions analysts face daily. You will learn to interpret results clearly and apply R insights to actual research, reports, and organisational strategy.
⚡ Your Lead Facilitator
Lead Facilitator
- PhD
- Research Leader
Dr. Braimoh Bello
A practitioner who has shaped policy and health outcomes across the globe — bringing lived expertise into every session.
CREDENTIALS
Institutional Appointments
- Research Technical Leader — CESAR
- Honorary Lecturer — Wits School of Public Health
GLOBAL CONSULTING
- UNAIDS
- Global Fund
- WHO
Trusted advisor to some of the most influential bodies in global health
UNAIDS
Global Fund
WHO
WORLD-CLASS EDUCATION
Academic Pedigree
- PhD — Utrecht University
- Business Leadership — Harvard University
- Artificial Intelligence — Oxford University
PUBLISHED AUTHORITY
Research Output
SCIENTIFIC PAPERS
TECHNICAL REPORTS
+
CONFERENCE PRESENTATIONS
+
Dr. Bello is not only a technical expert in research and evaluations but also a fantastic teacher.
Participant’s Testimonials
Don't Just Take Our Word For It
CESAR has grown into one of Africa’s most trusted providers of research and statistical courses. We’re also among the continent’s leading data analyst trainers, known for a practical teaching approach that consistently delivers results.
“I learnt more than i expected and the training sparked a lot of interests. Very important training that i wish i learnt what i learnt earlier. Thank you very much.”
Course participant, Zambia National Public Health Institute
“Facilitator is knowledgeable and highly skilled.”
Course participant, Zambia National Public Health Institute
“Informative, educational and insightful.”
Course participant, National Institute for Communicable Diseases, South Africa
“Excellent training, excellent facilitators, and especially impressive to have provided files with the slide and content of the course, and flash drives with the datasets. All in all, very professional. Furthermore, one walks away from the training feeling confident that one has a handle on the software and the principles involved in qualitative data analysis.”
Course participant, National Institute for Communicable Diseases, South Africa
“I would recommend the course to other technicians from RBC, Ministry of Health, and other ministries like Agriculture and Education. This course is important for public institutions.”
Course participant, Rwanda Biomedical Centre
“I’m more confident with R now than before. I now have the skill to search for manipulations and codes I didn’t know about before. I will be able to present data to my supervisors in a better explainable way.”
Course participant, CDC, Zambia
⚡ Secure your spot
Enroll in our “Comprehensive Data Analysis Course Using R” today and join the ranks of skilled professionals making a significant impact in their careers.
Frequently Asked Questions
Find answers to common questions about the comprehensive Data Analyst course with R
This course provides a complete overview of data analysis using R, covering data cleaning, visualization, statistical modeling, and advanced analytics. It’s designed to help learners become proficient in using R for real-world data analysis.
The course covers setting up and working efficiently in R and RStudio, importing and cleaning data using Base R and the tidyverse, and conducting exploratory data analysis. Participants will learn to summarise and transform data, manage datasets effectively and create data visualisations using ggplot2. Participants will master descriptive statistics and subgroup analysis. The course also cover hypothesis testing and common statistical tests using R.
Yes, the course is designed for both beginners and those with some experience. It starts with the basics of R programming and data analysis, then progresses to more advanced topics.
Traditional in-person training is scheduled for 23–27 March
No prior knowledge of R is required, but a basic understanding of statistics will be helpful.
The course is divided into multiple modules, each focusing on a specific area of data analysis. Each module includes video lectures, hands-on coding exercises, quizzes, and a final project.
You will need R and RStudio installed on your computer. R is the programming language, while RStudio is a user-friendly development environment for R.
Yes, we provide several data sets for hands-on practice, which are relevant to the topics covered in each module.
Yes, upon successful completion of the course and all assessments, you will receive a certificate of completion.
Absolutely! The certificate can be shared on your resume and LinkedIn profile to showcase your expertise in R and data analysis.
If you encounter any technical issues, you can reach out to our support team via email. Most issues are resolved within 24 hours.