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.
Faculty Professor Ralf A. Wilke Department of Economics, CBS Prerequisites Estimation of and Inference for the multiple regression model (OLS, 2SLS, LPM, F-,t-,LR-,Wald-, LM-tests), Maximum Likelihood Estimation, Regression with Binary Dependent Variable, Matrix Algebra, Basic concepts of asymptotic theory (consistency and asymptotic normality). The course is compulsory for the PhD students of Copenhagen Business School’s […]
The A2S2 Seasonal School provides a technically grounded introduction to AI alignment, safety and security, focusing on the whys and hows of making AI systems robust, appropriate, and aligned with human or application goals. While mental health is used as one motivating high-stakes application, the methods, concepts and evaluation frameworks generalize to a wide range […]
Enrolment guidelines This is a toolbox course where 80% of the seats are reserved to PhD students enrolled at the Faculty of SCIENCE at UCPH and 20% og the seats are reserved to PhD students from other Danish Universities/faculties (except CBS). Anyone can apply for the course, but if you are not a PhD student […]
Welcome to Generative AI in the PhD process Generative artificial intelligence (GAI) is becoming ingrained in research processes to an ever-evolving degree. Recently, GAI has recently become both the object for increased research, used as a research method, e.g. in the form of AI-assisted qualitative data analysis, and as a writing aid in the preparation of […]
Enrolment guidelines The module is mandatory for all new PhD students enrolled at Science from 1 January 2024 as part of the course 'Fundamentals of the PhD education at SCIENCE'. If you are a double degree student with a foreign host, you can not enroll in this course. Learning objectives The learning outcomes for the […]
Welcome to Mathematical Kaleidoscope III (2026) The five subjects to be covered by the course are described below. 1. J. Eduardo Vera-Valdés: Missing data and multiple imputation methods. 2. Charisios Grivas: Resampling techniques in Statistics and Data science. 3. Claus Dethlefsen: Trends in Pharmaceutical Statistics for Regulatory Submissions. 4. Matteo Bonini: Error correcting codes and their cryptographic applications […]
Driven by the technological progress, biology continuously undergoes a revolution that started in the late 1990s with the sequencing of the human genome. This revolution is on a scale that constantly redefines our basic understanding of biology and reaches deep into human and animal science, for example with respect to diseases and nutrition. Understanding the […]
Aim Qualitative methods offer to gain new insights into exploring what motivates individual understanding and behavior. As part of the course students will be introduced to grounded theory (coding) --a widely used systematic analysis of qualitative data. Grounded theory provides structured approach (through coding) to identify deep-seated influential themes and shared socio-cultural (mental) models and […]
Enrolment guidelines This is a toolbox course where 80% of the seats are reserved to PhD students enrolled at the Faculty of SCIENCE at UCPH and 20% of the seats are reserved to PhD students from other Danish Universities/faculties (except CBS). Seats will be allocated on a first-come, first-served basis and according to the applicable […]
Anomaly detection is highly important in many machine learning-driven fields, yet developing mostly independently for different data modalities such as audio, EEG signals, images, text, videos or time-series in general. This workshop aims at bringing together experts in anomaly detection from different communities and at promoting joint research activities of its members.
Enrolment guidelines This 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. Please read under "Participants". All applicants will be put on the waiting list until enrollment deadline. The course is free of charge for PhD students at Danish […]
Objectives of the course: In the field of Agroecology, rigorous data-driven research has become crucial for addressing complex agricultural and environmental challenges. The ability to effectively manage and analyse data is paramount for producing high-quality research outcomes and making informed decisions. Main course: Hands-on data: an applied statistics PhD course Aim: Provide the participants with a […]
The course will provide an introduction to the statistical software R for people with a basic knowledge of statistical concepts. R has become the lingua franca in statistics and many applied fields. The flexibility and large number of user-contributed packages makes it an extremely useful statistical toolbox for almost any data analysis and visualization problem.Disclaimer: […]
Multiple Correspondence Analysis (MCA) is a geometric data analysis technique designed to uncover patterns and structures in complex categorical datasets. Rooted in the tradition of French data analysis pioneered in the 1960s by French statistician Jean-Paul Benzécri, MCA represents data as clouds of points in a multidimensional space. The position and distance between these points […]
The course Discussing AI: Architecture, Art, and Research introduces AI as a potential collaborator in the creative process. Taking a comprehensive, multidisciplinary approach, it brings together artistic, scientific, and philosophical perspectives to explore the role of AI in creative research and practice. Emphasis is placed on discussion and critical reflection on both the possibilities and […]
Welcome Methods of AI in Modern Data Management Systems Description: This course is at the intersection of AI and data system design. The basic idea is to learn where the application (!) of AI methods may benefit the design of specific components of a data management system. The students will learn about opportunities as well as […]
The aim of the course is to introduce the student to machine learning techniques and enable the student to apply these methods to analyze complex data sets as typically encountered in modern research. The student will achieve an understanding of the theoretical background of supervised- and unsupervised machine learning techniques and will gain practical experience […]
Enrolment guidelines This is a specialised course. This means that 80% of the seats are reserved to PhD students enrolled at the Faculty of Health and Medical Sciences at UCPH and 20% og the seats are reserved to PhD students from other Danish Universities/faculties (except CBS). The course is free of charge for PhD students […]
Welcome to Data Science using R Description: In todays data-driven world, the ability to handle quantitative data systematically and reproducibly using reliable software is essential. This course, Data Science with R, is designed to introduce you to R, a powerful and free programming environment that has been a cornerstone of data analysis and statistical methodology for […]
Enrolment guidelines This 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 […]
Welcome Methods of AI in Modern Data Management Systems Description: This course is at the intersection of AI and data system design. The basic idea is to learn where the application (!) of AI methods may benefit the design of specific components of a data management system. The students will learn about opportunities as well as […]
Welcome to Introduction to Probabilistic Machine Learning Description: Machine learning (ML) and artificial intelligence have had major impacts on all areas of society and across research disciplines. Probabilistic ML provides a principled approach, based on probabilistic methods, to develop intelligent systems that make optimal decisions under uncertainty. Many problems in science can be casted as decision […]
This course aims to impart knowledge about and give participants an introduction to and practical experience using artificial intelligence (AI) tools to enhance their scientific and academic writing process.Disclaimer: DDSA has explicit permission from Arcanic and the owners of the https://phdcourses.dk/ website to display the courses on ddsa.dk.
Enrolment guidelines This 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 […]
Welcome to Reinforcement Learning Description: An intelligent system is expected to generate policies autonomously to achieve a goal, which is mostly to maximize a given reward function. Reinforcement learning is a set of methods in machine learning that can produce such policies. To learn optimal actions in an environment that is not fully comprehensible to itself, […]
This course aims to impart knowledge about and give participants an introduction to and practical experience using artificial intelligence (AI) tools to enhance their scientific and academic writing process.Disclaimer: DDSA has explicit permission from Arcanic and the owners of the https://phdcourses.dk/ website to display the courses on ddsa.dk.
Enrolment guidelines The module is mandatory for all new PhD students enrolled at Science from 1 January 2024 as part of the course 'Fundamentals of the PhD education at SCIENCE'. If you are a double degree student with a foreign host, you can not enroll in this course. Learning objectives The learning outcomes for the […]
Enrolment guidelines This is a specialised course where 50% of the seats are reserved to PhD students enrolled at the Faculty of SCIENCE at UCPH and 50% of the seats are reserved to other applicants. Seats will be allocated on a first-come, first-served basis and according to the applicable rules. Anyone can apply for the […]
Enrolment guidelines This 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 […]
Welcome to Data management and documentation using redcap and stata Program: Epidemiology and Biostatistics Description: The course will provide the participants with hands-on experience in handling data collected in REDCap, setting up forms, documenting the data management process and exporting data to use in e.g. STATA. The course provides an overview of the audit trail […]
Enrolment guidelines This is a specialised course where 50% of the seats are reserved to PhD students enrolled at the Faculty of SCIENCE at UCPH and 50% of the seats are reserved to other applicants. Seats will be allocated on a first-come, first-served basis and according to the applicable rules. Anyone can apply for the […]
Enrolment guidelines This is a toolbox course where 80% of the seats are reserved for PhD students enrolled at the Faculty of SCIENCE at UCPH and 20% of the seats are reserved for PhD students from other Danish Universities/faculties (except CBS). Seats will be allocated on a first-come, first-served basis and according to the applicable […]
Welcome to Machine Learning (2026) Description: Machine learning revolves around creating computer programs that enable machines to learn from examples or experiences. It's an interdisciplinary field at the intersection of computer science, engineering, statistics, and pattern recognition. In recent decades, it has witnessed rapid theoretical progress and extensive real-world applications across various domains. These applications encompass […]
Learn about bioinformatics analysis of genomic, transcriptomic, and proteomic data. During this course, you will gain knowledge of the most essential databases and methods for molecular sequence and structure analysis. These years, computer based methods play a crucial role in molecular biology, microbiology, and personalised medicine. Huge international databases of sequence and structure contain information, […]
Learn to analyse large data sets and train machine learning methods. Increasing amounts of data are being collected in the healthcare system from high throughput genomics, wearable devices, and electronic patient records. This course will provide you with the necessary data science skills required to analyse such large datasets. We will cover the various data […]
DDSA is thrilled to announce the dates of D3A – Danish Digitization, Data Science and AI 4.0 – hosted by Danish Data Science Academy, Pioneer Centre for AI, and Digital Research Centre Denmark! On October 8 and 9, 2026, we are bringing together visionary researchers and leading professionals at Hotel Nyborg Strand to grow the […]