The digital learning format "Automated Machine Learning" is intended to support future developers in the field of machine learning to make important design decisions automatically based on predefined data sets in order to achieve the best possible results in a short time when developing ML applications. The course, which is based on an offline event, is designed in such a way that it can be offered by universities in blended learning format with face-to-face and online phases or can be taken as part of a MOOC in self-study.
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Hyperparameter Optimization
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Neural Architecture Search
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Meta & Transfer-Learning
By the end of the course, you‘ll be able to...
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identify possible design decisions and procedures in the application of ML.
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implement the automatic optimization of design decisions.
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evaluate the design decisions made.
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Basics in Machine Learning (ML) and Deep Learning (DL)
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First experiences in the application of ML & DL
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Python programming language
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Optional: Basics of Reinforcement Learning
