Centre for Quantitative Analysis & Decision Support



The CQADS external training program is on hiatus and will return in September 2019 with "Hands-On Data Discovery: Data Analysis and Data Science Pipelines in R and Python", a 30-hour training module focusing on practical aspects of data analysis with 20 fully worked out data analysis  Jupyter notebooks (and opportunities to apply the pipelines to other datasets).  

Audience: This course is targeted at individuals who would like to explore methods to extract actionable insight from data. Having had some exposure to data is an asset, but not a necessity.    

Level: This course is not lecture-based and contains very little theory. While some background material will be provided in the form of slide decks and suggested readings, the focus remains firmly on building data analysis pipelines and applying algorithms to datasets. 

Pre-requisites: Programming know-how is not required but may be helpful, as would a quantitative background (economics, accounting, finance, statistics, mathematics, computer science, physics, sociology, etc.). 

Topics: Programming Basics of R, Data Collection, Data Processing and Visualization, Classification, Clustering, Association Rules Mining, Value Estimation, Deep Learning, Big Data, Time Series Analysis, Statistical Analysis, and other selected data science topics.

Cost: 1200$ per participant + HST. 

IT Requirements: participants must provide a laptop with wifi connectivity. No software installation required. 

A regular 10-week session will be run at Carleton once a term (Fall, Winter). On-site training also available (suggested schedules: 10 weekly 3-hour sessions, 15 weekly 2-hour sessions, 5 full days, etc.).  

Contact cqads [at] carleton.ca for information (starting in September 2019).

In the meantime, please visit the Data Action Lab, DataCamp, Coursera, and similar organizations for quality data science, A.I., and analytics training.