ITI9004《Mathematical foundations for data science and AI》是 莫纳什大学 的公开课程页面。当前可确认的信息包括 6 学分,难度 难,公开通过率 68%。 页面已整理 13 周教学安排,3 个重点考核,方便你快速判断工作量、考核结构和适配度。 课程简介摘要:Mathematical topics fundamental to computing and statistics including 。
Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per teaching period typically comprising a mixture of scheduled online and face to face learning activities and independent study. Independent study may include associated reading and preparation for scheduled activities. The unit requires on average three/four hours of scheduled activities per week. Scheduled activities may include a combination of teacher directed learning and online engagement.
Explain fundamental concepts in calculus including basic differentiation and integration, and composite, inverse and parametric functions;
Use trees and graphs to solve problems in computer science;
Describe the principles of elementary probability theory, evaluate conditional probabilities and use Bayes' Theorem;
Apply counting principles in combinatorics;
Demonstrate basic knowledge and skills of linear algebra, including the manipulation of matrices, solution of linear systems, and evaluate and apply determinants;
Perform key skills in the calculus of functions of several variables including the calculation of partial derivatives, find tangent planes and identify stationary points, root findings and convexity for optimisation.
