MAT9004 - Mathematical foundations for data science - 2018

Mathematical topics fundamental to computing and statistics including trees and other graphs, counting in combinatorics, principles of elementary probability theory, linear algebra, and fundamental concepts of calculus in one and several variables.

Upon successful completion of this unit, students should be able to:

1. use trees and graphs to solve problems in computer science;
2. apply counting principles in combinatorics;
3. describe the principles of elementary probability theory, evaluate conditional probabilities and use Bayes' Theorem;
4. demonstrate basic knowledge and skills of linear algebra, including the manipulation of matrices, solution of linear systems, and evaluate and apply determinants;
5. explain fundamental concepts in calculus including basic differentiation and integration, and composite, inverse and parametric functions;
6. 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.

On-campus: Examination (3 hours): 60%; In-semester assessment: 40%

Monash Online: In-semester assessment: 100%

Minimum total expected workload equals 144 hours per semester comprising:

1. Contact hours for on-campus students:
   • Three hours/week lectures
   • One and half hours/week laboratories
2. Contact hours for Monash Online students:
   • Two hours/week online group sessions

   Online students generally do not attend lecture, tutorial and laboratory sessions, however should plan to spend equivalent time working through resources and participating in discussions.

3. Additional requirements:
   • A minimum of 7.5 hours per week of personal study (22 hours per week for Monash online students) for completing lab/tutorial activities, assignments, private study and revision, and for online students, participating in discussions.

See also Unit timetable information