1. Introduction: Systems Thinking in Data-Driven Engineering [PDF]
- Modern analytical architectures
- Mapping data pipelines to use cases
- Assessment: Concept map of a smart engineering system
2. Managing data for data driven engineering [PDF] [PDF]
- Data collections life cycle
- Data and processes curation
- Data curation & processes curation
- Quantitative vs Qualitive Approaches
- Provenance and reproducibility
3. Designing experiments [PDF]
- Data Science Pipeline: definition and phases
- Data analytics algorithms, models and tools
4. From cleaning to prediction in practice [PDF]
- Data cleaning, preparation and quality
- Exploring and preparing data collections for building corpora
- Data Quality: bias & responsibility
- Understanding datasets
- Statistical method
- Machine learning method
- Prediction with linear regression and random forest
- Communicating results