Login for PhD students at UCPH
Login for others
Home
Course Catalogue
Communication & Teaching
Online Courses
Responsible Conduct of Research
Specialist Courses
Statistics
PhD Supervision for Academic staff
Course fee, cancellation policy and invoice details
How to apply for a course
PhD students from NorDoc universities
Newly enrolled PhD students at SUND
PhD students at UCPH
Other applicants
How to log on to the course system
How to log in as a student
How to log in as a course provider
Contact information
Processing...
Python Tsunami - Part 1
Provider: Faculty of Health and Medical Sciences
Activity no.: 3924-25-00-00
There are 27 available seats
Enrollment deadline: 28/02/2025
Date and time
17.03.2025, at: 08:00 - 19.03.2025, at: 16:00
Regular seats
35
Course fee
3,840.00 kr.
Lecturers
Anders Krogh
ECTS credits
2.20
Contact person
HeaDS Administration E-mail address: heads-admin@sund.ku.dk
Enrolment Handling/Course Organiser
PhD administration E-mail address: phdkursus@sund.ku.dk
Aim and content
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 enrollment deadline. After the enrolment deadline, available seats will be allocated to the waiting list.
The course is free of charge for PhD students at Danish universities (except Copenhagen Business School), and for PhD students at NorDoc member faculties. All other participants must pay the course fee
Learning objectives
A student who has met the objectives of the course will be able to:
1. Define and explain the use of basic programming concepts in Python, such as variables and data types and structures including lists, dictionaries, dataframes, etc. and perform elementary programming tasks needed for data analysis in Python.
2. Draw on online resources, especially documentation of different packages and community help forums to debug Python programs and acquire new knowledge and skillsets.
3. Know the different use cases of key Python libraries for data collection and analysis, including pandas and plotly express.
4. Understand how to structure Python scripts and Jupyter notebooks and how to collaborate with others on Python code using Google Colaboratory.
5. Use Python for simple programming and data analysis tasks in relation to scientific research projects.
Content
The course will first introduce the programming language in general, its strengths and use cases, and we will demonstrate how to run Python code in Jupyter Notebooks using Google Colaboratory. The course will provide an overview of the fundamental Pythonic data types and data structures such as strings, floats, integers, Boolean, lists, dictionaries etc., and participants will learn about conditional statements, how to write loops and how to organize code in functions. Lastly, the course will cover several libraries, especially pandas and library plotly express, which allow for efficient data manipulation and visualization.
Participants
Seats: 35
The course is intended for PhD students at SUND who are interested in learning how to use Python and who have no prior experience with this (or any other) programming/scripting languages. The course teaches the fundamentals and is targeted towards medical and biological researchers, e.g. not targeted towards students in data science, although they are of course welcome to join the course.
Relevance to graduate programmes
The course is relevant to PhD students from the following graduate programmes at the Graduate School of Health and Medical Sciences, UCPH:
All graduate programmes
Language
English
Form
The course is a combination of:
1. Lectures (run in real time in Jupyter Notebooks on Google Colab).
2. In-plenum exercises which are introduced and discussed during the lectures.
3. Longer exercises done collaboratively in smaller groups of participants.
Course director
Anders Krogh,
Professor, Head of Center for Health Data Science,
Center for Health Data Science,
anders.krogh@sund.ku.dk
Teachers
Henrike Zschach
PhD, Data Scientist,
Center for Health Data Science,
henrike.zschach@sund.ku.dk
Inigo Prada
PhD, Postdoc,
Department of Computer Science,
inlu@di.ku.dk
Valentina Sora
PhD, Postdoc
Center for Health Data Science
vaso@di.ku.dk
Dates
17-19 March 2025 from 08:00 to 16:00.
Course location
Room TBD
Faculty of Health and Medical Sciences, Panum,
Blegdamsvej 3B, 2200 København.
Registration
Please register before 28 February 2025
Expected frequency
The course will run three times per year – once in the Fall and twice in the Spring.
Seats to PhD students from other Danish universities will be allocated on a first-come, first-served basis and according to the applicable rules.
Applications from other participants will be considered after the last day of enrolment.
Note: All applicants are asked to submit invoice details in case of no-show, late cancellation or obligation to pay the course fee (typically non-PhD students). If you are a PhD student, your participation in the course must be in agreement with your principal supervisor.
Search
Click the search button to search Courses.
Choose course area
Course Catalogue
Choose sub area
Communication & Teaching
Online Courses
Responsible Conduct of Research
Specialist Courses
Statistics
PhD Supervision for Academic staff
Course calendar
See which courses you can attend and when
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Processing...
RadEditor - HTML WYSIWYG Editor. MS Word-like content editing experience thanks to a rich set of formatting tools, dropdowns, dialogs, system modules and built-in spell-check.
RadEditor's components - toolbar, content area, modes and modules
Toolbar's wrapper
Paragraph Style
Font Name
Real font size
Apply CSS Class
Custom Links
Zoom
Content area wrapper
RadEditor hidden textarea
RadEditor's bottom area: Design, Html and Preview modes, Statistics module and resize handle.
It contains RadEditor's Modes/views (HTML, Design and Preview), Statistics and Resizer
Editor Mode buttons
Statistics module
Editor resizer
Design
HTML
Preview
RadEditor - please enable JavaScript to use the rich text editor.
RadEditor's Modules - special tools used to provide extra information such as Tag Inspector, Real Time HTML Viewer, Tag Properties and other.
N
ew courses
Courses are published regularly. High demand courses are announced in spring and autumn.
Learn which courses are announced on fixed dates