This option proposes a selection of courses of statistics, data mining, algorithmics and data architectures that introduce the students to several facets of Data Science.
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The student may choose |
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De 20 à 30 CREDITS parmi | ||||||||
Annual block | ||||||||
1 | 2 | |||||||
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Algorithms in data science | Vincent Blondel , Jean-Charles Delvenne (coord.) , Gautier Krings | 30h+22.5h | 5 credits | 1q | x | x | |
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Machine Learning : regression, dimensionality reduction and data visualization | John Lee (compensates Michel Verleysen) , Michel Verleysen | 30h+30h | 5 credits | 1q | x | x | |
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Cloud Computing | Etienne Riviere | 30h+15h | 5 credits | 2q | x | x | |
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Databases | Siegfried Nijssen | 30h+30h | 6 credits | 2q | x | x | |
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Machine Learning :classification and evaluation | Pierre Dupont | 30h+30h | 5 credits | 2q | x | x | |
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Mining Patterns in Data | Siegfried Nijssen | 30h+15h | 5 credits | 1q | x | x | |
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Data mining & decision making | Marco Saerens | 30h+15h | 5 credits | 2q | x | x | |
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Statistical computing | Céline Bugli (compensates Bernadette Govaerts) , Bernadette Govaerts | 20h+20h | 6 credits | 1q | x | x | |
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Seminar in data management: basic | Catherine Legrand | 7.5h+10h | 5 credits | 1q | x | x |