from Scratch series on YouTube

Principal Component Analysis (PCA) - PCA is one of the most used statistical technique to explore high-dimensional data and large data sets to make them easier to interpret and analyze.

Pathway Enrichment Analysis (pathway ORA) - Enrichment (or over-representation) analysis is used to find if a group of genes share a common biological theme or pathway.

Setup a local Large Language Model (LLM) - LLMs are a type of deep learning models that are pre-trained on vast amounts of data. The underlying transformer is a set of neural networks that consist of an encoder and a decoder with self-attention capabilities.

RNA sequencing (RNA-seq) -  One of the most commonly used techniques in bioinformatics, RNA-Seq allows us to  analyze RNA abundance in a biological sample to study gene expression and cellular responses.

Lectures and Code are available for free, and are geared to give you a solid understanding of the topic discussed. I made them to supplement the bioinformatics lecture series. All lectures use R (or Python) to build the computational pipelines.