With jobs in Data Science ranked among the most lucrative, the competition is intensifying. This one-day workshop will introduce participants to the mindset necessary to stand out in Machine Learning challenges. It will be hosted by the founders of L2F-Learn to Forecast, a group of EPFL Mathematicians who came to prominence by winning the New York City Taxi Challenge on Kaggle in 2017 over more than 1200 teams. L2F now has 25 employees and delivers advanced ML solutions to large international corporations and institutions; it recently won the Siemens Competition on IoT and Predictive Maintenance in Berlin.

Each L2F founder will lead a team of participants and compete against the others. The goal will be to analyse a curated ATP World Tour data set and come up with powerful predictions and winning strategies. The most creative thinking will make the difference!

Solid understanding of the data science process: problem understanding, data understanding, exploratory data analysis, feature engineering, modeling, value creation. Special emphasis on brainstorming and team collaboration.

• Basic knowledge of Machine Learning
• Experience with Python (numpy, pandas, scikit-learn)
• Personal computer, with Jupyter Notebook installed