Register Today: Data Science and Analytics Workshops
The Centre for Quantitative Analysis and Decision Support (CQADS), located at Carleton University, with the support of CATAAlliance is offering a series of workshops this Fall on Data Science and Analytics, and on their applications for decision making in the real world. This 3-day series of workshops will run October 24-26 on campus, and is open to interested parties in the public and private sectors.
1. Introduction to Analytics: Preparing and Visualizing Data
An introduction to the notions that must be mastered prior to, and after, embarking on data analysis, along with a discussion of common challenges and pitfalls.
2. Mining for Information Gold: Data Science Concepts and Techniques
An introduction to the fundamental data science concepts involved in data mining, with a detailed discussion of three common analytical concepts: classification, clustering, and association rules.
3. Simple Data Discovery: Exploring Data with R
The goal of this workshop is to give participants some introductory experience extracting patterns and knowledge from real datasets using R, in order to increase their understanding of how data science can provide insight into problems.
4. Getting Technical: More Data Science Methods
A continuation of the introduction of data science concepts started in workshop #2, with a detailed discussion of seven specific methods/concepts which are commonly used by data scientists: support vector machines, artificial neural networks, logistic regression, naive Bayes classifiers, random forests, hierarchical clustering, and density clustering.
Pre-requisites, intended audiences, and outlines can be found here.
$1800 + HST per person.
Includes coffee/snacks, lunch each day, as well as a welcome reception and dinner on October 24th, and course materials.
Registration deadline is October 15th, 2016.
Space is limited to 25 participants, so be sure to register early.
(For information about registering to individual workshops, please contact firstname.lastname@example.org)