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- Data Carpentry1
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- Data analysis
- DNA-seq2
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- Machine Learning, Introductory, Novice / Entry-level, Supervised learning, Unsupervised learning, Principal Component Analysis, K-means, Hierarchical Clustering, Decision Trees, Random Forest, Regression1
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- United Kingdom1
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Target audience
- post-docs
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- This course is aimed at individuals working across life sciences who have little or no experience in bioinformatics. Applicants are expected to be at an early stage of using bioinformatics in their research with the need to develop their knowledge and skills further. No previous knowledge of programming is required for this course; group projects may give you the opportunity to learn basic programming, but participants will be supported in this by their mentors. Depending on your chosen project, an introductory programming tutorial may be given as homework prior to attending the course.2
- Biotechnology Companies1
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- Master students1
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- PhD students and young researchers in the life science and computational biology field who are planning to use RNA-seq data and are looking for the best practices to analyze these types of data1
- Pharmaceutical Industry1
- Postdoctoral Researchers1
- Researcher in life sciences1
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- This course is aimed at individuals working across biological sciences who have little or no experience in bioinformatics. Applicants are expected to be at an early stage of using bioinformatics in their research with the need to develop their skills and knowledge further. No previous knowledge of programming / coding is required for this course.1
- post-doctoral researchers and principle investigators working in wet-lab biology. Participants who are looking for a basic introduction to the bioinformatics resources offered by the EMBL-EBI and want to know more about accessing biological data and tools.1
- postdoc1
- postdocs.1
- postdoctoral researchers1
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- principle investigators1
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