PATH 411 Applied Data Science in Molecular Medicine Units: 3.00
The course introduces data science tools and methods to handle, process and extract knowledge and insights from large molecular medicine datasets. The focus will be on applying statistics, machine learning and related methods for the analysis of various research datasets and digital pathology.
Learning Hours: 120 (18L12pC, 84 Group Learning, 6 Online Activity, 36 Private Study)
Requirements: Prerequisite BIOL 243/3.0 or ECON 250/3.0 or GPHY 247/3.0 or HSCI 190/3.0 or NURS 323/3.0 or POLS 285/3.0 or PSYC 202/3.0 or SOCY 211/3.0 or STAT 263/3.0 or STAM 200/3.0.
Offering Faculty: Faculty of Health Sciences
Course Learning Outcomes:
- Perform basic programming and scripting (Mini Assignments 1 and 2, Group Assignments 1-3)
- Design experiment with data analysis in mind (Mini Assignment 2, Group Assignments 1-3)
- Perform data analysis that includes sequence alignment, data preprocessing, unsupervised and supervised learning and statatistics (Mini Assignments 1 - 3, Group Assignments 1 - 3)
- Work in a team to complete assignments, report and present results (Group Assignments 1 – 3)
- Assess and critique analytical methodology found in scientific publications (Paper critiques)