National course open for PhD students, postdocs, researchers and other employees in need of Advanced Python skills within all Swedish universities.
Important dates
Application now open!
Application closes: April 15, 2021
Confirmation to accepted students: April 21, 2021
For questions about the course, please contact Ashfaq Ali (ashfaq.ali@nbis.se), Sergiu Netotea (sergiu.netotea@nbis.se)
Course fee
The course is free of charge but a no show fee course fee of 2000 SEK will be invoiced to accepted participants who failed to attend the course after accepting to participate.
*Please note that NBIS cannot invoice individuals
The main aim of this course is to introduce students to the so-called Zen of Python for quick and clean application of python in data science. The workshop is structured around based on the industry way of classifying big data jobs: data analytics, data science, data engineering.
Participants will have an opportunity to learn the following topics
Learning Outcomes:
At the end of the course the course participants will have achieved following objectives
Workshop organization:
We aim for a balance between lecturing and exercise in Jupyter notebooks (jupyter.org) which is used for taking notes, self study, hands on tasks and interaction. Considering that the course is online, lectures will be delivered via zoom links and exercises will be carried out in zoom breakout rooms with the help of teaching assistants. Course session leaders will be available to answer theoretical and practical questions. Questions are welcome at any time.
You will be asked to prepare your laptop a week before the course starts. We will also use a slack channel for communication, posting links or code tips.
Important to Know:
The workshop covers some of the basic concepts of python programming and each session will have advanced material on the topic that may test the limits of the participant’s knowledge of python and computers. Difficulties during learning are expected and are part of the course design.
For the sessions on analyses of your own data, students are encouraged to send their topic of interest before the start of the course.
Entry requirements
Required for being able to follow the course and complete the computer exercises
Desirable to have
Due to limited space the course can accommodate a maximum of 20 participants. If we receive more applications, participants will be selected based on several criteria including entry requirements, motivation to attend the course as well as gender and geographical balance.
Github page (older version)
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