R Programming Foundations for Data Analysis
The course is addressed to individuals with little or no experience in programming but who are enthusiastic about learning how to use R for data analysis and streamline their work.
Events and courses
Bringing life science professionals together and furthering skills in the scientific community are in SciLifeLab’s DNA. Our many events and courses, which span a wide range of topics, present opportunities to develop your know-how and share your own experiences and network – sparking new ideas, as well as new collaborations.
Contact
events@scilifelab.se
education@scilifelab.uu.se
If you are part of the SciLifeLab community, you can submit an event to this calendar.
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Calendar of Events
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Introduction to Python – with application to bioinformatics
Introduction to Python – with application to bioinformatics
This course provides a practical introduction to the writing of Python programs for the complete novice. Participants are led through the core aspects of Python illustrated by a series of example programs.
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Introduction to Data Management Practices
Introduction to Data Management Practices
The workshop will introduce important research data management aspects through lectures, demonstrations, and hands-on computer exercises. The course is intended for researchers who want to take the first steps towards a more systematic and reproducible approach to analysing and managing research data.
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Introduction to bioinformatics using NGS data
Introduction to bioinformatics using NGS data
This intense one-week workshop provides an introduction to the analysis of next generation sequencing data. Lectures on the theory of concepts will be paired with practical computational exercises in the Linux environment.
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Introduction to bioinformatics using NGS data
NBIS/ELIXIR-SE Tools for Reproducible Research
NBIS/ELIXIR-SE Tools for Reproducible Research
NBIS / ELIXIR-SE course open for PhD students, postdocs, group leaders and core facility staff at all Swedish universities interested in making their computational analysis more reproducible. Important dates and information Application opens: 2024-08-26 Application closes: 2024-10-18 Confirmation to accepted students: 2024-10-25 Course Leader and teachers: In case you miss information on any of the above […]
Biostatistics and Machine Learning II
Biostatistics and Machine Learning II
This course expands on common life science data analysis methods, including dimensionality reduction techniques beyond PCA, mixed-effects models for analysis of repeated measures, and survival analysis. We will also dive deeper into machine learning, covering more classification algorithms, ensemble techniques, optimization strategies and PLS methods for single and multi-omics data analysis
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Last updated: 2024-09-18
Content Responsible: Maria Bäckström(maria.backstrom@scilifelab.uu.se)