Welcome to your calendar for data science events! Dive into a curated list of courses, conferences, seminars, workshops, and key deadlines. Tailor your search to match your interests by adjusting the event category filters. For those specifically looking for PhD courses, simply modify the filter settings to include these events as well. Stay connected and up-to-date with the latest in data science, all in one place.
ARCO (Algorithmic Research: Cooperation around Oresound) was established 2011 as a network for exchange of research within algorithms and to promote the general interest in this research area within the Oresund Region. The idea is to meet once or twice per year for a one-day workshop. On April 12th 2024, at the Royal Danish Academy […]
The complexity and scale of biological data are growing at an explosive rate. Currently, the main bottleneck towards new biological insights is often our ability to interpret existing data rather than limitations in the availability of data. In recent years, generative models have provided spectacular advances within various biological domains, and the community of researchers […]
The ProbAI is here to provide an inclusive educational environment that serves state-of-the-art machine learning and artificial intelligence expertise with a probabilistic twist. With a carefully designed curriculum and a seamless blend of theory and hands-on sessions, our expert team of invited lecturers will guide you through five intensive days each dedicated to a different […]
MAPSP is a biennial workshop dedicated to building a community of researchers interested in theoretical and practical aspects of scheduling, planning, and timetabling. The 16th Workshop on Models and Algorithms for Planning and Scheduling Problems (MAPSP 2024) will be organized at Hotel Koldingfjord, Kolding, Denmark. The impressive 1911 building of Hotel Koldingfjord is located right […]
This is a 2.5 ECTS PhD-course in advanced machine learning under the topic of "Physics meets Machine Learning". The course consists of five days (Monday-Friday, 9 AM - 4 PM) of lectures and exercises. The lectures will cover theoretical and practical aspects of prominent intersections between Physics and Machine Learning. Technical aspects, programming and application […]
A three-day workshop that brings together Danish and international researchers applying machine learning techniques to physics domains, including particle physics, astrophysics and cosmology, climate science, geophysics, molecular physics, quantum physics, condensed matter and biophysics. The program includes keynote speakers from ETH Zurich, Columbia University and DeepMind, fireside chats, research speed-dating, student lightning talks, and a […]
This course is supported by Danish Data Science Academy (DDSA) Registration: https://phd.moodle.aau.dk/course/view.php?id=2422 Lecturer(s): Associate Professor Roman Jurowetzki (Aalborg University Business School) Associate Professor Rolf Lyneborg Lund (Department of Sociology and Social Work, Aalborg University) Assistant Professor Mathieu Jacomy (Department of Culture and Learning, Aalborg University) Numbers of seats: 21 - We will contact you after […]
Aim and contentThis is a generic course. This means that the course is reserved for PhD students at the Graduate School of Health and Medical Sciences at UCPH. Anyone can apply for the course, but if you are not a PhD student at the Graduate School, you will be placed on the waiting list until […]
The 6th Nordic Fintech Research Symposium will focus on how academia, fintechs, larger financial institutions and authorities can collaborate on fighting financial fraud with a special focus on Anti Money Laundering (AML) by applying knowledge from state-of-the-art research and advanced industry solutions For the Symposium Copenhagen Fintech has worked with The Department of Computer Science […]
Aim and contentThis course is free of charge for PhD students at Danish universities (except Copenhagen Business School), and for PhD Students from NorDoc member faculties. All other participants must pay the course fee.Anyone can apply for the course, but if you are not a PhD student at a Danish university, you will be placed […]
Welcome to Machine learning in health technology Program: BEN Description: Do you want to get into machine learning but do not know where to start? This is a 3-day course with a practical approach to machine learning directed to PhD students at the Faculty of Medicine. The course includes two days of lectures from basics about machine learning to […]
Welcome to Self-Supervised Learning Organizer: Zheng-Hua Tan Lecturers: Zheng-Hua Tan ECTS: 2 Date/Time: November 18-20, 2024 Deadline: 28 October 2024 Max no. Of participants: 50 Description: The course gives an introduction to self-supervised learning methods for learning representations of single- and multiple-modality data, covering deep architectures, training target and loss functions used in state-of-the-art methods, and selected downstream applications. A focus will be […]
Aim and contentThis course is free of charge for PhD students at Danish universities (except Copenhagen Business School), and for PhD Students from NorDoc member faculties. All other participants must pay the course fee.Anyone can apply for the course, but if you are not a PhD student at a Danish university, you will be placed […]
Welcome to Modelling, Verification, Performance Analysis, Refinement, Synthesis and Machine Learning for Cyber Physical Systems Organizer: Kim Guldstrand Larsen Lecturers: Kim Guldstrand Larsen, Marius Mikucionis, Peter Gjøl Jensen, Ulrik Nyman ECTS: 3 Date/Time: 2, 3, 4, 5, 6 December 2024 Deadline: 11 November 2024 Max no. Of participants: 30 Description: Timed automata and games, priced timed automata and energy automata have emerged […]
Welcome to 3rd symposium on the advances in biomedical engineering and neuroscience Program: BEN - MANDATORY COURSE FOR BIOMEDICAL ENGINEERING AND NEUROSCIENCE Description: The course has a focus on disseminating the most relevant and recent achievements within biomedical and engineering science to address relevant health care problems. This course will be organized annually and will include […]