PIMS - CANSSI USaskatchewan Data Science Bootcamp

Data science is an interdisciplinary field that combines perspectives from mathematics, statistics and computer science. The focus is to extract and communicate meaningful information from complex data using techniques that fall under the umbrella of these three disciplines. The scope of the field is expanding, as learning from data is common practice in all disciplines. With the increasing availability of data with wide ranging characteristics, there is now a high demand for data scientists. The proposed summer school will expose participants to some core areas of data science, including real data analysis and hands-on training in software.

Bootcamp Topics:

• Data Visualization (mathematical foundations for high-dimensional data visualization; large-scale network embedding algorithms; big data processing techniques for real-time interactive visualization; cartographic representations and storytelling with data; interactive data visualizations using Jupyter and Paraview).
• Statistical Methods for High-throughput Data (multiple hypothesis testing; false discovery rate; q-value; generalized linear models; regularized regression methods; high-throughput data techniques, including gene expression, RNA-seq, and SNP array; software tools for handling high-throughput data).
• Introduction to Machine Learning(classification; clustering and dimensionality reduction; Bayes prediction; neural network; deep learning; reinforcement learning; machine learning with R).
• Data Science Case Studies (presentation of case studies based on real data; application of data sciencetechniques; hands-on training to solve study-specific problems and reproduce results using Jupyter, Paraview or R)