Schedule

Important dates (more info during the class)
  • Monday the 5th of May: Written exam (in-class)
  • Wednesday the 21th of May: Project report deadline
  • Sunday the 25th of May: Slides submission deadline
  • Monday the 26th of May: Presentations of the projects
Week Date Topic Lecture Slide Lecture Note Lab
1 Mon, Feb 17 Introduction +
EDA		 🧑🏻‍🏫 Introduction

🧑🏻‍🏫 EDA

 📄 Introduction

📄 EDA
2 Mon, Feb 24 Models
(regression & classification)		 🧑🏻‍🏫 Intro to Models

🧑🏻‍🏫 Linear & Logistic Models

🤖 ML_LinLogReg.R

🧑🏻‍🏫 Trees

🤖 ML_Trees.R

 📄 Intro to Models

📄 Linear & Logistic Models

📄 Trees
3 Mon, Mar 3 Lab 1

📝 Lab 1 Setup: Slides

📝 Lab 1 Intro to Quarto: Slides

💻 Setup

💻 LinLogReg

💻 Tree
4 Mon, Mar 10 Metrics
(& Overfitting detection)		 🧑🏻‍🏫 Neural Networks

🤖 MyNN.ipynb

🧑🏻‍🏫 Support Vector Machines

🤖 ML_SVM.R

 📄 Neural Networks

📄 Support Vector Machines
5 Mon, Mar 17 Lab 2

💻 NN

💻 SVM

💻 Scoring
6 Mon, Mar 24 Data splitting +
Ensemble methods		 🧑🏻‍🏫 Metrics

🤖 ML_Metrics.R

🧑🏻‍🏫 Data Splitting

🤖 ML_DataSplitting.R

 📄 Metrics

📄 Data Splitting

Mon, Mar 31 Interpretable ML 🧑🏻‍🏫 Ensemble Methods

🤖 ML_Ensemble.R

🧑🏻‍🏫 Interpretable ML

🤖 ML_Interpretability.R

 📄 Ensemble Methods

📄 Interpretable ML
7 Mon, Apr 7 Unsupervised Learning 🧑🏻‍🏫 Intro to Unsupervised Learning

🧑🏻‍🏫 Clustering

🧑🏻‍🏫 Dimension Reduction

 📄 Intro to Unsupervised Learning

📄 Clustering

📄 Dimension Reduction
8 Mon, Apr 14 Lab 3

💻 Splitting

💻 Ensemble

💻 VarImp
9 Mon, Apr 21 Easter
(i.e., no lecture) 😊


10 Mon, Apr 28 Lab 4 +
revisions

💻 Clustering

💻 PCA
11 Mon, May 5 Written exam
(on site) ❗


12 Mon, May 12 Working session
(projects)


13 Mon, May 19 Working session
(projects)



1 Wed, May 21 Project report deadline
(moodle) ❗



1 Sun, May 25 Project presentation deadline
(moodle) ❗


14 Mon, May 26 Final presentations
(on site) ❗


1 📩 Report & Slides submission at 23:59
Lecture Slides vs Lecture Notes

The most up to the date content of the course are found in the lecture slides. The lecture notes are only there to assist you, and may contain outdated (but still correct) information. Therefore, always refer to the lecture slides for the most accurate and up to date content.

Note

The content of the schedule may be adapted (faster or slower).