Description This course focuses on the fundamentals of Data Science methods to extract nontrivial, previously unknown, and potentially useful information from databases. It covers data exploration and preparation, data visualization, and computing with data using machine learning algorithms for tasks such as classification, clustering, and outlier detection in structured datasets, along with model evaluation techniques. Requisites Complete the following:CS2040 - Algorithms I (3)CS2910 - Introduction to File and Database Management (3)MA1200 - Linear Algebra I (3)ST2520 - Introduction to Applied Statistics ll (3) Course Timetable A3 Tue, Thu from 11:30 to 12:50 Jan 6 2025 - Apr 23 2025 Grande Prairie Campus Room B201 Instructor MMirbagheri Closed: 20 of 20 spots filled Add to timetable add A3 Fri from 10:00 to 11:20 Mon from 11:30 to 12:50 Jan 6 2026 - Apr 23 2026 Grande Prairie Campus Room G111 Room G111 Instructor MMirbagheri Closed: 20 of 20 spots filled Add to timetable add L1 Thu from 15:00 to 17:50 Jan 6 2025 - Apr 23 2025 Grande Prairie Campus Room A307 Instructor MMirbagheri Closed: 20 of 20 spots filled Add to timetable add L1 Thu from 14:30 to 17:20 Jan 6 2026 - Apr 23 2026 Grande Prairie Campus Room G111 Instructor MMirbagheri Closed: 20 of 20 spots filled Add to timetable add Course Outlines Find out everything you need to know about your upcoming or past courses. Understand the learning outcomes, evaluation methods, delivery mode, and prerequisites. View all historical course outlines
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