Dr Lorenzo Picinali
The module aims to provide students with sufficient tools and techniques to explore small and large datasets, to perform data analysis and to use key insights from statistics and machine learning.
The main topics include the basics of data analysis, statistics, and advanced data science.
During the whole module, tutorials will be structured around case studies that are appropriate for Design Engineering students, such as social media activity analysis.
On completion of this module, students will be better able to:
- Apply basic descriptive and inferential statistical analysis and data visualisation techniques
- Apply simple machine learning techniques
- Interpret the results of such methods and techniques, and report them appropriately
- Solve practical problems using different analytical techniques
- Apply such methods using Python and Matlab
Description of Content
Basic of data analysis:
Introduction to descriptive statistics
Introduction to inferential statistics
Advanced data science:
Supervised learning: classification
Overfitting and feature selection
Train, test and validation sets