Course Schedule

Spring

• Mathematics for Machine Learning (4hp) First time: 2022
• Introduction to logic for AI (2hp) First time 2022
• Artificial Intelligence and Machine Learning (6hp) First time: 2022
• Software Engineering and Cloud Computing (6hp) First time: 2022
• Ethical, Legal, and Societal aspects of AI and Autonomous Systems (3hp) Given yearly from 2022

Autumn

• Autonomous Systems (6hp) First time: 2022

Spring

• Deep Learning (6hp)
• Interaction, Collaboration, Simulation and Visualization (6hp) First time: 2023

Autumn

• Graphical Models, Bayesian Learning and Statistical Relational Learning (6hp)
• WASP Project Course (6hp)
• Topological Data Analysis (6hp)

Spring

• Learning Theory (6hp) First time: 2022
• Deep Learning for Natural Language Processing (6hp)

Autumn

• Reinforcement Learning (6hp) First time: 2022
• Scalable Data Science and Distributed Machine Learning (6hp)
• Learning Feature Representations (6hp)

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This course is mandatory for the AI-track and elective for the AS-track. The course is offered in the spring 2021 and is organized into three different modules.

For current information please check this year’s course page:

https://kth.instructure.com/courses/29062

The Modules are found in the calendar 2021 and the items are described here:

Deep Learning & GANs, Module 1

Deep Learning & GANs, Module 2

Deep Learning & GANs, Module 3

The invitation will be distributed via e-mail in March.

This course is mandatory for the AS-track and elective for the AI-track.

For more information visit the calendar 2021.

The invitation has been distributed via e-mail.

IMPORTANT INFORMATION!

The course will be given online 1-2 October 2020. Those who were registered for the postponed meeting in Umeå 19-20 March 2020 were informed via mail.

Organization

This course is mandatory for the AI-track and elective for the AS-track.

Course coordinator/examiner: Virginia Dignum: virginia.dignum@umu.se

The course is organized in one module.

Time: 1-2 October 2020 (Online)

Visit the course page for more information: Ethical, Legal, Societal and Economical Aspects of AI (3hp)

IMPORTANT INFORMATION!

Due to the coronavirus outbreak, we have decided to arrange all three modules of “Learning Theory and Reinforcement Learning” online, possibly in a live streaming manner during April 1-2 (Module 1), and May 5-6 (Module 2) and May 14-15 (Module 3), so please keep the dates.

This means that you will not have to book travel/accommodation for the three modules. We are sorry in case you already made a booking, but hope for your understanding, given the circumstances.

Organization

This course is mandatory for the AI-track and elective for the AS-track.

The course is offered in spring 2020 and organized into three different modules:

Module 1 – Mathematical Foundations of ML

Arranged by: Cristian Rojas crro@kth.se, April 1-2

Module 2 – Supervised and Unsupervised Learning

Arranged by: Alexandre Proutiere alepro@kth.se, May 5-6

Module 3 – Reinforcement Learning

Arranged by: Johannes Andreas Stork johannesandreas.stork@oru.se,  May 14-15

Visit the course page for more information: Learning Theory and Reinforcement Learning (6hp)

Organization

This course is mandatory for the AI-track and elective for the AS-track.

The course is offered in autumn 2020 and organized into three different modules:

Module 1 – Introduction to Data Science: Introduction to fault-tolerant distributed file systems and computing. September 17-18, Online.
Arranged by: Raazesh Sainudiin – raazesh.sainudiin@math.uu.se

Module 2 – Distributed Deep Learning: Introduction to the theory and implementation of distributed deep learning. October 22-23,  Online.
Arranged by: Amir H. Payberah – payberah@kth.se

Module 3 – Decision-making with Scalable Algorithms. November 19-20, Online
Arranged by: Raazesh Sainudiin – raazesh.sainudiin@math.uu.se

Visit the course page for more information: Scalable Data Science and Distributed Machine Learning (6hp)

IMPORTANT INFORMATION!

This course was originally designed as an on-site event. We now plan to offer all three modules remotely, with a mix of pre-recorded lectures and interactive lab sessions via Zoom. This means that you will not have to book travel to/accommodation in Linköping. Registered participants will receive further information via mail.

Organization

This is an elective course for the AI-track. The course will be taught jointly by Marco Kuhlmann and Richard Johansson

The course is offered in spring 2020 and organized into three different modules:

Module 1: Introduction to deep learning and NLP, March 30-31

Module 2: Structured prediction problems in NLP, April 27-28

Module 3: Generation problems in NLP, May 25-26

Visit the course page for more information: Deep Learning for Natural Language Processing (6hp)

Organization

This is an elective course for the AI-track. The course will be taught at Linköping University and Chalmers jointly by Michael Felsberg, Per-Erik Forssén, and Christopher Zach.

The course is offered in autumn 2020 and organized into three different modules:

Module 1: Energy-based representation learning, September 28-29, Online

Module 2: Learning generative and discriminative appearance models, October 26-27, Online

Module 3: Representations of motion and geometry, December 7-8, Linköping

Visit the course page for more information: Learning Feature Representations (6hp)

Organization

This course is mandatory for AS-track and elective for the AI-track.

Course coordinator/examiner: Patric Jensfelt, Bo Bernhardsson

The course is offered in spring 2020 and includes two meetings:

Meeting 1: February 13-14

Meeting 2: April 16-17 CANCELLED

Visit the course page for more information: Autonomous Systems 1 – Sensing, Perception, Control and Decision Making (6hp)

Organization

This course is mandatory for AS-track and elective for the AI-track.

Course coordinator/examiner: Patric Jensfelt, Bo Bernhardsson

The course is offered in autumn 2020 and includes two meetings. The first meeting is, however, cancelled.

Meeting 1: October 8-9 CANCELLED

Meeting 2: November 26-27 Norrköping

Visit the course page for more information: Autonomous Systems 2 –  Learning, Knowledge, Interaction and Collaboration

Organization

Examinator: Daniel Axehill

Visit the course page for more information: WASP Project Course (6hp)

Organization

Examinator: Daniel Axehill

Visit the course page for more information: WASP Project Course (6hp)