DATA601
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Working with Data and Visualization
Computer Science
SC - Faculty of Science
Subject
DATA - Data Science
Description
An introduction to fundamental data science concepts including basic data organization, data collection, and data cleaning. Provides a review of basic programming concepts in Python, as well as an introduction to problem-solving concepts including algorithmic complexity, recursion, vectorization, and regular expressions. Covers the fundamentals of data visualization and critical thinking.
Prerequisite(s): Admission to the Graduate Certificate in Fundamental Data Science and Analytics, or the Graduate Diploma in Data Science and Analytics, or the Master of Data Science and Analytics.
Prerequisite(s): Admission to the Graduate Certificate in Fundamental Data Science and Analytics, or the Graduate Diploma in Data Science and Analytics, or the Master of Data Science and Analytics.
Course Attributes
Fee Rate Group(Domestic) - H, Fee Rate Group(International) -G, GFC Hours (3-0)
Courses may consist of a Lecture, Lab, Tutorial, and/or Seminar. Students will be required to register in each component that is required for the course as indicated in the schedule of classes. Practicums, internships or other experiential learning modalities are typically indicated as a Lab component.
Component
LEC
Units
3
Repeat for Credit
No
Subject code
DATA
Understanding Course Information
Please refer to Course Terminology and Description to better understand how to interpret course information such as GFC Hours, pre-requisites, course levels, etc.