data_wrangling

Data Wrangling Course assignments

The Course includes 3 Assignments:

1. Assessment 1: Pre-processing data project Assessment type: Written report using R Markdown

Course learning outcomes

• Utilise leading open-source software, R, to address and resolve data wrangling tasks
• Select, perform, and justify data validation processes for raw datasets to satisfy quality requirements
• Apply and evaluate the best practice standards of Tidy Data Principles

2. Assessment 2: Coding exercises Assessment type: Written report using R Markdown

Course learning outcomes

• Utilise leading open-source software, R, to address and resolve data wrangling tasks
• Select, perform, and justify data validation processes for raw datasets to satisfy quality requirements
• Apply and evaluate the best practice standards of Tidy Data Principles
• Critically analyse data integration procedures for combining data with different types and structures into a suitable format

4. Assessment 3: Applied relational data project Assessment type: Written report using R Markdown and video presentation

Course learning outcomes

• Utilise leading open-source software, R, to address and resolve data wrangling tasks
• Select, perform, and justify data validation processes for raw datasets to satisfy quality requirements
• Apply and evaluate the best practice standards of Tidy Data Principles
• Critically analyse data integration procedures for combining data with different types and structures into a suitable format