Educational Resources

If you consider joining my team, make sure you're familiar with the following resources:

• HDR-UK Summer School (2019): [GitHub Enterprise] R Course on Introduction to Machine Learning (by Adriano Barbosa);
• Cambridge University Autumn (2019): [GitHub] Introduction to Machine Learning for biomedical data analysis in Python (by Adriano Barbosa);
• Python data science handbook (Jake VanderPlas);
• NumPy is the fundamental package for scientific computing with Python;
• Matplotlib is a Python 2D plotting library which produces publication quality figures;
• Pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language;
• Scikit-Learn - Machine Learning in Python;

• R Tidyverse Packages;
• R Markdown;

• Git - distributed version control system;
• Jupyter Notebooks - interactive data science and scientific computing across all programming languages.