Data models and methods, module 2
The course is meant for everyone interested in the application of machine learning methods to biomedical data.
Mode of delivery
Course study period
This course is part of a study module:
- Bioinformatics and data analysis training module 25 ects (Academic Year 2022-2023)
Neural network architectures, activation functions, loss functions, batch sizes, gradient descent algorithm, learning rates, back propagation, overfitting, regularization, Keras and Tensorboard.
Academic Year 2022-2023
Field of study
Prerequisities and co-requisites
It is recommended that this course is taken after the courses “Data models and methods, module 1” and “Data analysis in practice, module 1” from the continuous education programme in bioinformatics and data analytics. It is recommended that this course is taken together or after the course“Data models and methods, module 2” from the continuous education programme in bioinformatics and data analytics.