Third party funded individual grant
Start date : 01.09.2019
End date : 31.08.2020
This course offers an overview of some of the most widely used machine learning methods that are necessary to know in order to be able to work on data science applications. We present the necessary fundamental for each topic and provide coding exercises in order to practice the models.
The course includes:
1) The common practices for data collection, anomaly detection and signal fusion.
2) Teaching different tasks regarding regression, classification, and dimensionality reduction using methods including but not limited to linear regression and classification, Support vector machines and Deep neural networks.
3) Introduction to Python programming for data science.
4) Applying machine learning models on real world engineering applications.