A range of 6 subjects in Data Analytics, Data Mining and Machine Learning will give students the chance to develop skills and expertise, broaden their international experience and capitalize on knowledge opportunities.
The subjects have been selected so that they provide an engaging and high impact educational experience that will enable them to make progress towards their degree or expand their academic and/or professional life and experience.
- Weak supervision for data extraction, data cleaning, and machine learning, by Christopher Ré
- The Power of Visual Analytics: Unlocking the Value of Big Data, by Daniel A. Keim
- Crowd Data Sourcing, by Sihem Amer-Yahia
- Time Series Understanding, and data quality, by Chris Williams
- Learning from our movements – Mobility data analytics, by Yannis Theodoridis
- Ethics of Data Driven Innovation, by Natasa Milic-Frayling
Participants should bring their own laptop, which they should use during the exercises and other hands-on work they will do during the School.