Jyväskylä Summer School Course: Data analytics + Machine Learning + Optimisation

Course: Data analytics + Machine Learning + Optimisation (4 ETC cr)
Lecturer:  Manuel López-Ibáñez
Contact info and CV: http://lopez-ibanez.eu
Dates:  August 13-17, 2018
Abstract: This course covers all the steps that go from accessing data about a problem to analysing the data, using it for prediction and classification and designing and testing an optimisation algorithm to solve it, using Python as the main programming language.  We will introduce fundamental concepts in data analytics, modelling, machine learning and optimisation, and how they relate to each other.  In addition, the course will discuss all those practical details that are often left out from textbooks, but are crucial for successfully solving an optimisation problem. Finally, the course will include many examples of pitfalls and recommended practices when designing, testing and comparing optimisation methods, in particular metaheuristics, such as local search and evolutionary algorithms, for both single-objective and multi-objective problems.
Participants: master’s students / doctoral students / post-docs – application system is open till April 30, 2018
Further information: Course identifier: COM2 on page https://www.jyu.fi/en/research/summer-and-winter-schools/jss/courses/courses-in-computational-sciences