Introduces deeper tools, skills, and techniques for collecting, manipulating, visualizing, analyzing, and presenting a number of different common types of data. With a data life-cycle perspective, looks into data elicitation and preparation as well as the actual usage of data in a decision-making context. Introduces techniques for visualizing and supporting the interactive analysis and decision making on large complex datasets. Focus on critical thinking and good analysis practices to avoid cognitive biases when designing, thinking, analyzing, and making decisions based on data.
This course may not be repeated for credit.
Prerequisite(s)
- Data Science 601, 602, 603, 604 and admission to the Graduate Diploma in Data Science and Analytics or the Master of Data Science and Analytics with a specialization in Data Science.
Sections
| LEC 1 | MW 17:00 - 19:45
| TI STUDIODE
| Aditya Nittala | | |
| Notes: Please refer to your Student Centre for fees associated with this class. This information will be available before the first day of classes. |
This course will be offered next in
Winter 2024.