The R Programming for Data Analytics Training Course is a comprehensive, practice-focused programme designed to develop strong analytical capabilities using the R programming language. This course provides a structured pathway from foundational R concepts to advanced data analytics techniques, enabling participants to work confidently with data across its full lifecycle. Learners gain hands-on experience in data import, cleaning, manipulation, visualisation, and statistical analysis, all within the R environment. Emphasis is placed on writing efficient, reproducible code and interpreting analytical outputs for real-world decision-making.
Delivered by Imperial Corporate Training Institute. Throughout the course, participants explore how R is applied in modern data analytics across industries such as finance, healthcare, marketing, government, and research. The curriculum integrates core R syntax with powerful libraries such as tidyverse, dplyr, ggplot2, and caret, ensuring learners understand both the technical and analytical dimensions of data work. By the end of the programme, participants are equipped to transform raw data into meaningful insights, build analytical models, and communicate results clearly through visual and statistical reporting.
Objectives
- Develop a solid understanding of R programming fundamentals for data analytics
- Learn to import, clean, and manage structured and unstructured datasets
- Apply data wrangling techniques using modern R libraries
- Create clear and insightful data visualisations for analytical reporting
- Perform descriptive and inferential statistical analysis in R
- Build and evaluate predictive models using R-based techniques
- Understand how to automate and reproduce analytical workflows
- Interpret analytical results to support evidence-based decision-making
- Apply R programming skills to real-world data analytics scenarios
- Strengthen problem-solving and analytical thinking using data-driven methods
Target Audience
- Data analysts seeking to enhance their analytical skills using R
- Professionals working with data in finance, healthcare, marketing, or operations
- Business analysts aiming to incorporate advanced analytics into their roles
- Researchers and academics handling quantitative data
- IT professionals transitioning into data analytics roles
- Graduates and early-career professionals pursuing careers in data analytics
- Government and public-sector staff involved in data-driven planning
- Anyone interested in learning R for practical data analytics applications