In September 2018, Pine Biotech started a pilot course on Machine Learning for Biomedical Data at the Georgetown University Medical Center offered to the Masters Systems Medicine Program. A limited number of students are being accepted to join this project-based educational experience.
The goal of this pilot is to establish a training pipeline for students interested in research and industry applications of Machine Learning. A hype associated with Machine Learning and Artificial Intelligence is exposing a new audience to the significance, but also limitations of these methods. Our course is designed to allow all participants to find out for themselves how most commonly used machine learning methods could be applied to high-throughput biomedical data.
In this course, we will cover:
- Data visualization Techniques
- Unsupervised Machine Learning: Clustering
- Supervised Machine Learning: Classification
- Feature selection and gene signature construction
- Regression, generalized linear models (GLM). Factorial, ANOVA
- Network analysis
- Introduction to “Deep” Learning
After completing this course, students will have the opportunity to use the T-BioInfo MultiOmics platform to analyze their own dataset and apply developed skills to real-world challenges. This course is a part of the OmicsLogic Training program launched in 2017 by Pine Biotech in collaboration with the Tauber Bioinformatics Research Center at Univeristy of Haifa, Israel.