BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//DDSA - ECPv6.18.0//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://ddsa.dk
X-WR-CALDESC:Events for DDSA
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Europe/Copenhagen
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20230326T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20231029T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20240331T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20241027T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20250330T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20251026T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20260329T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20261025T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20270328T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20271031T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;VALUE=DATE:20260907
DTEND;VALUE=DATE:20260916
DTSTAMP:20260728T114737Z
CREATED:20260728T114737Z
LAST-MODIFIED:20260728T114737Z
UID:10001845-1788739200-1789516799@ddsa.dk
SUMMARY:Machine learning with sports and health data - Introduction and practical implementation in R (7/9 + 10/9 and 15/9 2026)
DESCRIPTION:Over the last five to ten years machine learning (ML) methods has gained widespread use with both sports and health data. ML methods can be used with both accelerometry or heart rate data for health or sports purposes or for simple clinical studies to find important patterns in the data. The possibilities seem almost endless. An important strength of the ML methods is that it can model highly complex data\, which is common attribute of most sports and health data. However\, the introduction of engines like the ChatGPT or Bard also suggests that understanding the strengths and weaknesses of this branch of statistical methods is important to disseminate quality health and physiological information from the sports and health data.\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/machine-learning-with-sports-and-health-data-introduction-and-practical-implementation-in-r-7-9-10-9-and-15-9-2026/
LOCATION:SDU\, Odense                Campusvej 55
CATEGORIES:PhD Course
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20260520
DTEND;VALUE=DATE:20260523
DTSTAMP:20260902T103741Z
CREATED:20260420T112409Z
LAST-MODIFIED:20260902T103741Z
UID:10001789-1779235200-1779494399@ddsa.dk
SUMMARY:An Introduction to Genomics in Health Science (20-22/5 2026)
DESCRIPTION:This 3-day course aims at introducing to biomedical researchers a foundational understanding of genomics\, epigenomics and transcriptomics\, laboratory techniques\, and motivating practical applications in disease and health researches. \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/__trashed-142__trashed-2/
LOCATION:SDU\, Odense                Campusvej 55
CATEGORIES:PhD Course
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20260303
DTEND;VALUE=DATE:20260312
DTSTAMP:20260205T125018Z
CREATED:20260115T115134Z
LAST-MODIFIED:20260205T125018Z
UID:10001865-1772496000-1773273599@ddsa.dk
SUMMARY:Reproducible data analysis in Stata (3/3 +10/3+11/3 2026)
DESCRIPTION:A scientific article typically provides the first table presenting characteristics for the study population. The characteristics include for example frequencies for categorical variables\, mean and standard deviations for continuous variables\, p values etc. There should also include tables typically presenting results out of several statistical analyses. The ideal reproducible data analysis requires that the whole working process from data cleaning to the published results should be reproducible without any copy-and-paste because it is well-known that copy-and-paste Stata output can be not only tedious and time-consuming but also error prone. Therefore\, workout a sequential Stata do-files automatically export both the descriptive and the analytical output is crucial not only to align with the principles of reproducible data analysis but also make the working process much more efficient.\nDisclaimer:\nDDSA 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/__trashed-122/
LOCATION:SDU\, Odense                Campusvej 55
CATEGORIES:PhD Course
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20250401
DTEND;VALUE=DATE:20250402
DTSTAMP:20250210T115319Z
CREATED:20250210T115319Z
LAST-MODIFIED:20250210T115319Z
UID:10001448-1743465600-1743551999@ddsa.dk
SUMMARY:Data Science Day at SDU - co-located with IEEE ICSA 2025
DESCRIPTION:The International Conference on Software Architecture (https://conf.researchr.org/home/icsa-2025)\, a prominent event in the fields of software engineering and architecture\, is coming to Denmark for the first time\, and you won’t want to miss it! The conference will be hosted by SDU in Odense from March 31 to April 4\, 2025. \nDDSA is sponsoring “Data Science Day” on April 1\, co-located with ICSA 2025. A variety of engaging activities are planned for that day\, including workshops and tutorials focused on data science and machine learning\, a special talk by Len Bass\, a tour of SDU labs\, and social events. Participation on April 1 (Data Science Day) is free of charge. Please register using the following link before February 27: https://sdu.conferencemanager.dk/?eventcode=DataScienceDay
URL:https://ddsa.dk/event/data-science-day-at-sdu-co-located-with-ieee-icsa-2025/
LOCATION:SDU\, Odense                Campusvej 55
CATEGORIES:DDSA-Funded Event
ATTACH;FMTTYPE=image/jpeg:https://ddsa.dk/wp-content/uploads/2025/02/DDSA-Data-Science-Day.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20240905
DTEND;VALUE=DATE:20240907
DTSTAMP:20240424T083818Z
CREATED:20240424T083818Z
LAST-MODIFIED:20240424T083818Z
UID:10001160-1725494400-1725667199@ddsa.dk
SUMMARY:Introduction to STATA (5 - 6/9 2024)
DESCRIPTION:The course is intended for beginners\, for those who want to brush-up their Stata skills\, and for those with knowledge about statistical models or methods who want to know how to implement them in Stata. It is specifically about using Stata rather than explaining statistical concepts or methods.\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-stata-5-6-9-2024/
LOCATION:SDU\, Odense                Campusvej 55
CATEGORIES:PhD Course
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20240514
DTEND;VALUE=DATE:20240516
DTSTAMP:20240424T082336Z
CREATED:20240424T082336Z
LAST-MODIFIED:20240424T082336Z
UID:10001161-1715644800-1715817599@ddsa.dk
SUMMARY:Basic Introduction to "R" (14-15/5 2024)
DESCRIPTION: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.\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/basic-introduction-to-r-14-15-5-2024/
LOCATION:SDU\, Odense                Campusvej 55
CATEGORIES:PhD Course
END:VEVENT
END:VCALENDAR