Fundamentals of Biomedical Sciences (6 credits)
The course offers a practical and comprehensive overview of the most fundamental topics necessary for modern Biomedical Scientists. We focus on key concepts, their supporting experimental evidence, and their application in contemporary research and clinical science. Students choose three of the four 2-credit courses (six credits total):
- BSR1030 Fundamentals of BMS I – Biochemistry & Molecular Biology
Concepts: Genetics, DNA and RNA regulation, Protein processing
- BSR1031 Fundamentals of BMS II – Pharmacology & Drug Discovery
Concepts: Receptor theory, Structure-based drug design, Pharmacokinetics
- BSR1032 Fundamentals of BMS III – Cell & Developmental Biology
Concepts: Cellular signaling, Cytoskeleton, Developmental Biology
- BSR1033 Fundamentals of BMS IV – Neuroscience
Concepts: Neurophysiology, Neuroanatomy, Plasticity
Computer Systems (3 credits).
This course provides an introduction to computer systems and scientific computing environments to enable effective use of computational and data resources. The course is divided into 3 units, each worth 1 credit:
- BDS1005 UNIX & Linux fundamentals
- BDS1006 Architectures & Applications in Scientific Computing
- BDS1007 Introduction to Scientific Programming in Python
Introduction to Algorithms (BDS2005, 3 credits)
This computer-science intensive course provides a survey of algorithms - that is, computational methods used to solve appropriately defined problems, and their implementation on modern scientific computing hardware.
Machine Learning for Biomedical Data Science (BDS3002, 3 credits)
This course is designed to train students in commonly used methods to organize, mine and learn from data sets, especially those that are complex and large (big data). These methods include classification, clustering, network inference and analysis, and outlier/anomaly detection.