Lectures on data science: Introduction and Fundamentals of Machine Learning

21 Mar 2024, 09:00 → 22 Mar 2024, 17:00 Europe/Berlin

GRS001 (RWTH Aachen)

Stefan Sandfeld

This course serves as an introduction to machine learning for beginners, spanning two days. 

The first day is dedicated to statistical machine learning methods such as linear regression and principal component analysis (PCA), taught through a mix of lectures and practical exercises. 

The second day introduces neural networks, starting from perceptrons and moving to fully connected networks, with each concept explained in lectures, followed by hands-on tutorials. Depending on the level and time left, convolutional neural networks (CNNs) could also be covered. 

The course is designed to build foundational knowledge in machine learning for those new to the field.

Thursday 21 March

1 Lecture: Introduction and Fundamentals of Machine Learning

Speaker: Prof. Stefan Sandfeld (FZJ, IAS-9)

2 Lecture: Linear regression

Speaker: Prof. Stefan Sandfeld (FZJ, IAS-9)

10:30 Break

3 Tutorial: Linear regression

Speaker: Tarek Iraki (FZJ, IAS-9)

12:00 Lunch break

4 Tutorial: Linear regression (cont’d)

Speaker: Tarek Iraki (FZJ, IAS-9)

14:00 Break

5 Lecture: Principal Component Analysis (PCA)

Speaker: Prof. Stefan Sandfeld (FZJ, IAS-9)

15:30 Break

6 Tutorial: Principal Component Analysis (PCA)

Speaker: Aytekin Demirci (Forschungszentrum Jülich)

Friday 22 March

7 Lecture: Perceptrons, Perceptron Learning, Multi Perceptron Learning

Speaker: Prof. Stefan Sandfeld (FZJ, IAS-9)

10:15 Break

8 Tutorial: Perceptrons, Perceptron Learning, Multi Perceptron Learning

Speaker: Aytekin Demirci (Forschungszentrum Jülich)

12:00 Lunch break

9 Lecture: Fully Connected Networks

Speaker: Prof. Stefan Sandfeld (FZJ, IAS-9)

14:00 Break

10 Tutorial: Fully connected networks

Speaker: Dr Bashir Kazimi (FZJ, IAS-9)

15:30 Break

11 Tutorial: Fully connected networks (cont'd)

Speaker: Dr Bashir Kazimi (FZJ, IAS-9)

Closing remarks and discussion