Making Coding Work for You

Coding and programming can be invaluable skills for scientists and engineers, but it’s important to know how to use them appropriately. How do we identify problems which may benefit from these tools? How can we choose which coding languages to learn, and how to best apply them to our research? Join us in this webinar to find out how researchers with little to no coding experience can build their skills and enhance their work! 

Dr Douglas Houston

KISS: Teaching Python to Absolute Novices

Our Introduction to Python Programming for Data Science is aimed at Data Science Technology and Innovation MSc students with no prior experience of programming. Therefore, the course consists of introductory learning material presented in the Python language. All teaching is delivered online through Learn, Collaborate and Jupyter Notebooks hosted on the CoCalc in-browser platform. Weekly online pair-programming sessions provide live interaction, and online discussion forums allow asynchronous communication. A strong emphasis is placed on self-guided learning, and the use of web resources such as search, Stack Exchange, Git Hub, Quora and various mailing lists.

Valentin Kapitany

Coding for Machine Learning In Science

The future of STEM is written in computer code. This is true for education, for academic research and technological industries. Indeed, after graduation, current STEM students will likely spend a significant portion of their careers coding. I’m a 3rd year PhD student focusing on machine learning, and one of the organisers of the ‘Machine Learning in Science’ at the University of Glasgow. So, in this talk, I will discuss some practical aspects of machine learning coding. We will focus on Python practices, data management, adapting online resources for your needs, and commenting and sharing your own code. 

Dr Aleksandra Nenadic

The Carpentries, and giving researchers the basic skills they need to tackle their data and computing challenges

Making research methods, data and results more accessible and reproducible can contribute to better science. Taking even small steps towards being more open, reproducible or even a bit better organised than the last time will make you more efficient in your work but will also help make the life easier for your future self or the person that comes to your group/lab after you. The Carpentries is a big international community of enthusiastic volunteers teaching foundational computational skills (version control, basic programming, command line, data organisation, cleaning, analysis and visualisation) founded on best practices (building modular and reusable code, using data structures, reproducibility) for researchers across disciplines. The emphasis is not on advanced, enterprise workflows or tools, but basic “toolbox” skills for everyday use that can be mastered in a relatively short period of time giving researchers the data organisation and computing skills they didn’t even know they needed.

Follow us on Twitter @CISMA_Colloquia.

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