Schedule

ImportantImportant dates (more info during the class)
  • Monday the 27th of April: Written exam (9h00-11h00, Room Internef-272)
  • Wednesday the 13th of May: Project report deadline
  • Friday the 15th of May: Slides submission deadline
  • Monday the 18th of May: Presentations of the projects
Week Date Topic Lecture Slide Lecture Note Lab
1 Mon, Feb 16 Introduction +
EDA		 🧑🏻‍🏫 Introduction

🧑🏻‍🏫 EDA

 📄 Introduction

📄 EDA
2 Mon, Feb 23 Models 🧑🏻‍🏫 Intro to Models

🧑🏻‍🏫 Linear & Logistic Models

🤖 ML_LinLogReg.R

🧑🏻‍🏫 Trees

🤖 ML_Trees.R

 📄 Intro to Models

📄 Linear & Logistic Models

📄 Trees
3 Mon, Mar 2 Lab 1

📝 Lab 1 Setup: Slides

📝 Lab 1 Intro to Quarto: Slides

💻 Setup

💻 LinLogReg

💻 Tree
4 Mon, Mar 9 Advanced Models 🧑🏻‍🏫 Neural Networks

🤖 MyNN.ipynb

🧑🏻‍🏫 Support Vector Machines

🤖 ML_SVM.R

 📄 Neural Networks

📄 Support Vector Machines
5 Mon, Mar 16 Lab 2

💻 NN

💻 SVM
6 Mon, Mar 23 Evaluation +
Lab 3		 🧑🏻‍🏫 Metrics

🤖 ML_Metrics.R

🧑🏻‍🏫 Data Splitting

🤖 ML_DataSplitting.R

 📄 Metrics

📄 Data Splitting

 💻 Scoring

💻 Splitting
7 Mon, Mar 30 Ensemble Models +
Interpretable ML +
Lab 4		 🧑🏻‍🏫 Ensemble Methods

🤖 ML_Ensemble.R

🧑🏻‍🏫 Interpretable ML

🤖 ML_Interpretability.R

 📄 Ensemble Methods

📄 Interpretable ML

 💻 Ensemble

💻 VarImp

Mon, Apr 6 Easter
(i.e., no lecture)


8 Mon, Apr 13 Unsupervised Learning +
Lab 5		 🧑🏻‍🏫 Intro to Unsupervised Learning

🧑🏻‍🏫 Clustering

🧑🏻‍🏫 Dimension Reduction

 📄 Intro to Unsupervised Learning

📄 Clustering

📄 Dimension Reduction

 💻 Clustering

💻 PCA
9 Mon, Apr 20 Revisions +
catching up


10 Mon, Apr 27 Written exam
(on-site) ❗


11 Mon, May 4 Working session
(projects, on-site+
online)


12 Mon, May 11 Working session
(projects, on-site+
online)



Wed, May 13 Project report deadline
(moodle) ❗



Fri, May 15 Project presentation deadline
(moodle) ❗


13 Mon, May 18 Final presentations
(on-site) ❗



Mon, May 25 Pentecost Monday
(i.e., no lecture) 😊


CautionLecture 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 The lecture notes are only there to assist you, and may contain outdated (but still correct) information.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).