This repository serves as a crash course designed for undergraduates joining CoCo lab (Or any interested student if they find it helpful). The aim is to help them familiarize themselves with the tools and technologies commonly used in the lab. The course includes the following topics:
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Introduction to Git (module1): Learn the basics of version control with Git.
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Introduction to Python (module2): Get started with Python programming, covering fundamental concepts and syntax ranging from python installation to different libraries and the use of VSCode and jupyter notebooks
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Getting Started with Python-MNE (module3): Explore the basics of working with Python-MNE for magnetoencephalography (MEG) and electroencephalography (EEG) data.
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Introduction to Compute Canada (module4): Understand the basics of accessing and utilizing resources on Compute Canada.
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Getting Started with Scikit-learn (module5): Learn the fundamentals of machine learning using Scikit-learn in Python and how to apply it for neuroscience.
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Introduction to Source Estimation (module6): Explore the concepts and usage of source estimation in Python.
Feel free to explore each module to access specific learning materials and resources. Follow the README files in each module for detailed instructions and guidance related to the respective topic. This crash course aims to provide a solid foundation for undergraduates entering CoCoLab, helping them navigate the tools and technologies essential for their work.