Somehow it’s already December, and 2025 is just around the corner! If learning to code has been on your to-do list, why not make it your New Year’s resolution? We’ve made it easy with three introductory coding courses in January, designed specifically
for biologists and genomic scientists. They’re the perfect way to kickstart your coding journey and enhance your research and analysis skills in the year ahead.
🔍 R for Biologists | 15-17 January
- Learn R from the ground up: objects, variables, and data types.
- Master data importing, cleaning, and manipulation.
- Create beautiful visualizations with ggplot2 and interactive plots.
- Bring your own data for personalized guidance in our data clinic!
🐍 Introduction to Python | 20-24 January
- Get started with Python and explore how it benefits bioinformatics research.
- Learn to manipulate text, work with files, and automate tasks with loops and conditions.
- Discover advanced topics like regular expressions, dictionaries, and filesystem operations.
- Gain practical skills to create efficient bioinformatics pipelines.
- IN PERSON course - the perfect excuse for a trip to beautiful Edinburgh to see off the January blues!
💻 Linux for Genomics | 29-30 January
- Navigate the Linux command line with confidence.
- Learn file management, permissions, and shell scripting.
- Explore essential tools for genomic data analysis, including seqtk, samtools, and bedtools.
- Boost your productivity by integrating Linux into your workflows.
🚀 Why Learn Coding with Us?
Our expert-led courses are tailored for researchers, offering practical, hands-on exercises and real-world applications in genomics and biology.
Looking to Advance Later in the Year?
Take your skills to the next level with our advanced coding courses:
Spaces are filling fast—don’t miss out!
Start your coding journey in 2025 with confidence! If you have any questions please don’t hesitate to reach out.
Kind regards,
Dr Kathryn Campbell
Genomics and Bioinformatics Training Coordinator - Edinburgh Genomics
School of Biological Sciences
University of Edinburgh
Email:
kcampb2@ed.ac.uk
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