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DTSTART;VALUE=DATE:20241106
DTEND;VALUE=DATE:20241121
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SUMMARY:Hands-on Introduction to Data Management Plans (DMPs)
DESCRIPTION:Copenhagen Centre for Social Data Science \nDates and time:\n Day 1 – Wednesday\, 6 November 2024 – 2:00 pm – 4:30 pm \n Day 2 – Wednesday\, 20 November 2024 – 2:00 pm – 4:00 pm \nGood research data management (RDM) practices are an essential part of good research practices. They increase the efficiency and quality of data collections and ensure secure handling and storage of data (to prevent data breaches\, misuse\, or loss) as well as compliance with requirements by research institutions\, publishers\, funders\, and legislation (e.g. GDPR). This course provides a hands-on training on best practices in managing research data (including quantitative and qualitative data)\, during which the course participants draft data management plans (DMPs) for their current research projects. \nAcademic aim: \n– Introduction to basic concepts and best practices in RDM\n – Drafting a DMP for a current research project and attaining the skills to write DMPs with ease\n – Gaining further knowledge about RDM requirements by the University of Copenhagen (UCPH)\, publishers\, funders\, and legislation (e.g. GDPR)\, and how to fulfil these  \nTarget group:  \nThe course is aimed at PhD students from the social sciences. It will among other things refer to specific requirements and processes at the UCPH and UCPH-Faculty of Social Sciences. It is\, however\, open to all PhD students and researchers who are looking for a hands-on training on best practices in RDM and drafting DMPs. No prior knowledge is required. \nCourse organisers and teachers:  \n– Siri Völker\, Special Consultant\, Data Manager at the Social Sciences Data Lab\, Copenhagen Center for Social Data Science\, University of Copenhagen\n – Joseph Burgess\, Senior Consultant\, Data Steward at SODAS and Team Leader at the Social Sciences Data Lab\, Copenhagen Center for Social Data Science\, University of Copenhagen\n   \nProgramme: \nDay 1 (6 November 2024) – Introduction to research data management (RDM) and data management plans (DMPs) \n2:00 – 2:45 pm  \n – Introduction to research data management (RDM):\n – What is RDM?\n – Why is RDM important?\n – Requirements for good RDM practices by the UCPH\, publishers\, funders\, and legislation (e.g. GDPR)\n – UCPH Policy for RDM and related processes\n – UCPH support services \n2:45 – 3:45 pm\n – Introduction to data management plans (DMPs):\n – What is a DMP?\n – Why is a DMP important?\n – How to draft a DMP? \n3:45 – 4:00 pm\n – The course participants receive the assignment to draft DMPs for their respective PhD projects to be discussed on day 2 \n4:00 – 4:30 pm\n – Voluntary: The course participants can start to work on their DMPs and clarify related questions with the presenters/data management experts \n Day 2 (20 November 2024) – Practical discussion of DMPs \n2:00 – 2:30 pm\n – Presentation of a best practice DMP \n2:30 – 3:45 pm\n – Discussion of the participants’ DMPs in groups with data management experts available to answer open questions \n3:45 – 4:00 pm\n – Wrap-up \n Language: English \nECTS: 0.5 \nMax. numbers of participants: 20 \nCourse fee: Free for PhD students at all Danish Universities\, except PhD students at CBS who will be charged a DKK 600 fee (1.200 per ECTS). \nRegistration: Please register via the link in the box no later than 2 October 2024 \nFurther information: For more information about the PhD course\, please contact the PhD Administration (phd@hrsc.ku.dk). \n  \nLiterature: \n– UCPH Policy for Research Data Management (intranet)\n – UCPH Data Management Plan Template v2.1 (intranet) \n  \n Disclaimer:DDSA has explicit permission from Arcanic and the owners of the https://phdcourses.dk/ website to display the courses on ddsa.dk.
URL:https://ddsa.dk/event/hands-on-introduction-to-data-management-plans-dmps/
LOCATION:City Campus (CSS)\, Øster Farimagsgade 5\,                Room: TBA
CATEGORIES:PhD Course
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DTSTART;VALUE=DATE:20240827
DTEND;VALUE=DATE:20240830
DTSTAMP:20260404T005545
CREATED:20240424T084517Z
LAST-MODIFIED:20240424T084517Z
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SUMMARY:Introduction to Machine Learning for the Social Sciences
DESCRIPTION:Copenhagen Centre for Social Data Science \nDates and time:\n 27-29 August 2024 from 9 am to 4 pm. \nThis course will introduce the basics of big data and machine learning and how it can be used in the context of social science research. No prior knowledge is assumed\, and it is well-suited for people with no prior experience using big data or machine learning. The course will cover different topics including how big data methods differ from inferential statistics\, data cleaning and pre-processing\, different machine learning models and explainable AI methods\, data ethics and privacy\, as well as bias and responsible AI. \nCore machine learning principles such as cross-validation\, out-of-sample prediction\, and hyper-parameter tuning will be introduced. A key focus will be on interpretable machine learning models such as regression-based models\, decision trees\, and random forests.        \nThe assessment will involve completing a machine learning analysis\, either in Python or in R. Therefore\, some prior experience with one of these coding languages is preferred. A basic understanding of inferential statistics is also preferred. Participants can bring their own data or use the data that will be provided.  \n Academic Aim:\n – To think critically about when Big Data and machine learning should be used for social science research (assess advantages\, disadvantages\, and limitations)\n – To be able to perform a machine learning analysis \nTarget group: Social science background. To gain most from the course some prior experience with R or Python and a basic understanding of inferential statistics is ideal. \nCourse organiser: Rosa Ellen Lavelle-Hill\, Assistant Professor\, Department of Psychology\, University of Copenhagen \n Disclaimer:DDSA has explicit permission from Arcanic and the owners of the https://phdcourses.dk/ website to display the courses on ddsa.dk.
URL:https://ddsa.dk/event/introduction-to-machine-learning-for-the-social-sciences/
LOCATION:City Campus (CSS)\, Øster Farimagsgade 5\,                Room: TBA
CATEGORIES:PhD Course
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