Data Skills Courses at ESS
The Essex Summer School (ESS) is introducing new Data Skills courses for professional development running from May to June 2025. This hybrid-format training consists of two course clusters, each containing three two-day modules, specifically designed for professionals seeking to enhance their data literacy and analytical capabilities.
The programme begins with Introduction to R and Basic Data Analysis (May 1-17), where participants transition to the powerful R programming environment. The final cluster, Intermediate Statistics with R (June 5-20), advances into more sophisticated analytical techniques and visualisation methods.
Each module runs for two consecutive days from 10 am to 5 pm, allowing for an intensive learning experience while maintaining flexibility for working professionals.
These clusters can be as an entire sequence, along, or you can choose modules individually.
Sessions available for both in-person and online participation.
Courses
A. Introduction to R and Basic Data Analysis (May 1-16)
Learn the basics of the powerful R statistical programming environment, along with the fundamentals of data manipulation and analysis. The ‘Foundations’ course (A) is not required, but recommended for those with no previous experience in data analysis.
Module A1 (May 1, 2): Introduction to the R Environment – Get started with R programming through hands-on practice and basic data operations.
Module A2 (May 8, 9): Data Manipulation with R – Learn data transformation and validation techniques to prepare data for analysis.
Module A3 (May 15, 16): Basic Statistical Analysis in R – Apply statistical methods and create professional visualisations.
B. Intermediate Statistics with R (June 5-20)
Intended for those who have taken the ‘Introduction’ course (B) above, these modules take your data skills to the next level with intermediate statistics using the R environment and more advanced visualisation, modelling, text processing, and automated reporting techniques.
Module B1 (June 5, 6): Data Visualisation with R – Create advanced visualisations and interactive graphics using specialised R packages.
Module B2 (June 12, 13): Data Analysis and Modelling in R – Explore regression analysis, time series, and predictive modelling techniques.
Module B3 (June 19, 20): Advanced Data Types and Reporting Workflows in R – Master automated reporting and interactive dashboards using R Markdown.
Course Fees
- Introduction to R – Monday, 28 April
- Intermediate Statistics with R – Monday, 2 June 2025
Apply here
If you are interested in these modules, contact us.
A. Introduction to R and Basic Data Analysis (May 1-16)
Module A1: Introduction to the R Environment (May 1,2)
This module introduces participants to R programming and the RStudio environment, focusing on basic syntax and data structures.
- Introduction to R and RStudio
- R syntax, data types, and basic operations
- Working with vectors, matrices, and data frames
- Control structures
- Writing functions in R
Module A2: Data Manipulation with R (May 8,9)
This module focuses on data manipulation techniques in R, introducing participants to powerful packages for data transformation.
- Reading and writing data in various formats
- Data cleaning and preprocessing
- Data validation
- Introduction to data manipulation with Base R and tidyverse
- Working with dates and times in R
Module A3: Basic Statistical Analysis in R (May 15,16)
This module covers fundamental statistical analysis techniques using R, building on the skills learned in previous modules.
- Descriptive statistics in R
- Probability distributions and random number generation
- Hypothesis testing
- Correlation analysis
- Simple linear regression
- Introduction to reporting outputs using R Markdown
B. Intermediate Statistics with R (June 5-20)
Module B1: Data Visualisation with R (June 5,6)
This module focuses on creating effective data visualisations using R, introducing participants to ggplot2, tidyverse, and other packages related to visualisation.
- Introduction to ggplot2 and the grammar of graphics
- Creating and customizing various plot types
- Advanced plotting techniques
- Interactive Visualisations with plotly
- Creating maps and spatial Visualisations
Module B2: Data Analysis and Modelling in R (June 12,13)
This module covers more advanced statistical techniques and expands on Module 3 and 6 content within the R environment.
- Advanced Regression Techniques
- MLE techniques
- Time Series and Panel Analysis
- Model Diagnostics
- Model Selection
- Hierarchical models
Module B3: Advanced Data Types and Reporting Workflows in R (June 19,20)
This module covers advanced data types and text analysis, teaching participants to work with complex data structures, regular expressions, and text analytics.
- Complex Data Structures
- Text Processing Fundamentals
- Unstructured Data Analysis
- Text Analytics Applications
- Dynamic and Automated Documentation and Reporting
