Lectures, labs and partial exams (quizzes) - an overview
Please note that you are strongly encouraged to attend all the lecture sessions on Campus. Also, it is vital that you watch the corresponding pre-recorded videos beforehand (if available) and read the recommended material.
Quizzes correspond to three partial exams scheduled on three specific dates throughout the course.
As for lab sessions, it is only mandatory to demonstrate five lab assignments (get them reviewed by teaching assistants) on selected occasions. So there is no need to attend all lab sessions. More information on bonus points that can be earned by early review of your lab assignments and about signing up for lab review on the selected time slots can be found in Lab review.
Lecture and lab plan
Lecture 1: Course introduction and fundamental concepts (Jan 15, kl. 8-10, K1)
Lecture 2a-b: From perceptron learning rule to backpropagation in feedforward networks - supervised learning (Jan 16, kl. 8-12, K2)
Lab (Jan 17)
Lecture 3: Generalization, regularization, model selection and validation (Jan 20, kl. 8-10, K1)
Lab 1a bonus point deadline (Jan 22, kl.8-12)
(Jan 23, kl.13-15, D2)
Lab (Jan 24)
Mandatory Quiz 1 (Jan 27, kl. 9-10 or 10-11) - please register at services (lecturers cannot register you for the exam!)
Lecture 4: Practical aspects of ANN approaches to pattern recognition problems (Jan 29, kl. 8-10, D2)
Lab (Jan 29)
Lecture 5: Radial basis function networks and introduction to unsupervised learning (Jan 30, kl.13-15, K1)
Lab 1b bonus point deadline (Feb 3, kl.8-12)
Lecture 6: Self-organising maps (Feb 5, kl.13-15, D1)
Lecture 7a: Hopfield networks and introduction to stochastic networks (Feb 5, kl.15-17, D1)
Lab (Feb 6)
Lecture 7b: Boltzmann machines and RBMs (Feb 7, kl. 8-10, K1)
Mandatory Quiz 2 (Feb 10, kl. 9-10 or 10-11) - please register at services (lecturers cannot register you for the exam!)
Lecture 8: Temporal processing with ANNs: feedforward vs recurrent network architectures (Feb 11, kl. 13-15, D2)
Lab 2 bonus point deadline (Feb 12, kl.15-17)
Lecture 9: Deep learning fundamentals (Feb 13, kl.13-15, K1)
Lecture 10a: Representation learning (Feb 14, kl.10-12, D2)
Lab (Feb 14. kl.10-12)
Lecture 10b: Representation learning and deep generative modelling (Feb 17, kl. 8-10, K1; Feb 20, kl.13-15, K1)
Lab 3 bonus point deadline (Feb 19, kl. 15-17)
Mandatory Quiz 3 (Feb 24, kl. 9-10 or 10-11) - please register at services (lecturers cannot register you for the exam!)
Lab (Feb 26)
Lab 4 bonus point deadline (Feb 27, kl. 8-12)
Lab (Mar 3) - catch-up lab
Lecture 11: Questions and review of past exams (Mar 4, kl. 8-10, D2)
Written exam (TEN3) on Mar 11, kl.8-11 - please register at services (lecturers cannot register you for the exam!)
Re-quiz examination (KON1) on Mar 14, kl.14-17 - please register at services (lecturers cannot register you for the exam!)
Extra lab review sessions after the exam, if needed, will be announced later.
Please find more details regarding the lecture content and recommended reading materials in respective lecture modules.