Johannes De Smedt

Johannes obtained his BSc and MSc in Information Systems Engineering, and his PhD in Applied Economics at KU Leuven, Belgium. He is currently the Dixons Carphone Lecturer in Business Analytics.
His research focuses on the discovery of flexible business process models from data generated by process-aware information systems. He also performs research on the integration of Internet-of-Things data into processes, as well as on many other problems in the decision modelling and mining area, including temporal item-set analysis.

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Predictive Analytics using Machine Learning (edX)

Learn how to build predictive models using machine learning. This course will give you an overview of machine learning-based approaches for predictive modelling, including tree-based techniques, support vector machines, and neural networks using Python.

Successfully Evaluating Predictive Modelling (edX)

Gain an in-depth understanding of evaluation and sampling approaches for effective predictive modelling using Python. A predictive exercise is not finished when a model is built. This course will equip you with essential skills for understanding performance evaluation metrics, using Python, to determine whether a model is performing [...]