Joining the lab might be overwhelming since we work on a broad range of applied molecular biology\nand bioinformatics. As most of incoming students may come from biomedical background, learning some\ntools as you join the lab will be very useful later on. I listed some of the useful tools below:
\nPython has been used in a lot of our development. Therefore, programming in Python is almost needed\nif you decide to join the lab. There are a lot of resources on how to learn Python. Try to\nlearn linear algebra, data science, and machine learning with some of the Python libraries such as\nnumpy, pandas, and scikit-learn.
Today, Machine Learning (ML) and Deep Learning (DL) are a popular tools to build models in many projects.\nUnderstanding the basis of these tools are useful. Make sure that you learn the core concept of learning algorithms before applying\nto your project. There are multiple free online classes that you can learn ML and DL such as Andrew Ng's Machine Learning, Neuromatch Academy, Deep learning's book by Goodfellow and Bengio,\nand more.
\n... I will continue adding more resources to this page.
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