Centre for Quantitative Analysis & Decision Support

Introduction to Data Science

          2017 Fall CQADS Workshop Series 
          Introduction to Data Science

          30 October to 3 November, 2017. Each day consists of 2 hours of theoretical instruction in the morning, followed by 2 hours of practical work in the afternoon

          Description:
          An introduction to the fundamental data science concepts involved in data analysis, with a detailed discussion of four common analytical
          concepts – visualization, classification, clustering and association rules.The application of these concepts will be illustrated through some
          simple toy examples, along with a discussion of common challenges and pitfalls.

          Goal:
          By the end of the workshop, participants will be able to appreciate the functionality of different types of data science concepts and
          recognize opportunities for their application when presented with real-world data.

          Intended Audience
          Individuals who wish to understand the functionality and capabilities offered by different data science concepts and methods, even if they won’t be the ones implementing them.

          Pre-Requisites
          This workshop requires very little mathematical or computer programming knowledge. Some experience with quantitative ideas is assumed.

          Schedule:
                Monday: AM - Introduction, Data Science Universals, Data Visualization
                Monday: PM - Basics of R, Simple Data Visualization
                Tuesday: AM - Fundamental Notions, Association Rules Mining
                Tuesday: PM - Data Manipulation in R, Association Rules Mining R packages, Case Study
                Wednesday: AM - Classification and Decision Trees, Clustering and k-Means
                Wednesday: PM - Decision Trees and k-Means R packages, Case Studies
                Thursday: AM - Support Vector Machines, Naïve Bayes Classification
                Thursday: PM - SVMs and NBC R packages, Case Studies
                Friday: AM - Density-Based Clustering, Spectral Clustering
                Friday: PM -  DBSCAN and SC R packages, Case Studies

          Cost per participant: $1800 + HST

          Includes:
                - free parking
                - daily coffee, snacks, and lunch
                - course materials
                - 2-week access to the workshop Python/R Notebooks on the CQADS server

          A limited number of fellowships are available to the Carleton community. Inquire at cqads@carleton.ca for more information. 

          Online registration for this workshop opens on September 1, 2017 and closes on October 25, 2017 (select the F17: Basics of Data Science option).