Foundation unit for MDataSc and GDDS to make a one-unit combination from MAT1830 and MAT1841 and streamline students mathematical preparation. This unit will replace MAT2004 from Semester 1, 2017.

Assessment loading has changed to 60/40 since there is now a university requirement that final exams not be 70%. The final examination should remain 3 hours. This is *NOT* a change.

The reasons for this *non-change* are:

We are testing not just conceptual understanding but also ability to work things out. Calculations and deductions take time.

Time pressure in mathematics is a disaster because questions go pear-shaped if you make a minor error early in a calculation or miss some subtlety of the question. This may result in a lot of wasted time trying to make something work when it isn't going to, or in having to do a question completely again from the start. Redoing questions in this way is common on maths exams.

There are lots of concepts in MAT9004. We go a little way into a lot of different directions. In fact there are elements of numerous very different branches of mathematics (calculus, linear algebra, probability, combinatorics, graph theory etc). To get coverage of a healthy fraction of these concepts requires a longer exam. If the coverage is less it disadvantages students whose strengths are not tested, and introduces a larger luck factor in the final results.

14/09/2018 - Admin: updating CE and workload to reflect new activity types as per university policy.

24/9/2019: Admin - adding 10 minutes reading time to the overall exam duration as per University requirements.

16/09/2020 - Admin: Update to include new assessment and teaching approach fields as per Handbook requirements.

01/10/2020 - Admin: Update unit name to include AI as this unit will also be part of the foundation units in C6007 MAI from 2021.

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.

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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.

On-campus, Monash Online

Taught by School of Mathematical Sciences, at Level 2 (AQF7) foundation unit for Master of Data Science and GDDS.

Monash Online: Problem-based learning.

On-campus: Problem-based and peer assisted learning.

On-campus: Examination (3 hours and 10 minutes): 60%; In-semester assessment: 40%

1. Continuous assessment: part 1 - 10% - ULO: 5
2. Continuous assessment: part 2 - 15% - ULO: 4, 6
3. Continuous assessment: part 3 - 15% - ULO: 1, 2, 3
4. End of semester examination - 60% - ULO: 1, 2, 3, 4, 5, 6

Monash Online: In-semester assessment: 100%

1. Assignment 1 - 30% - ULO: 4, 5
2. Assignment 2 - 30% - ULO: 2, 3, 4, 6
3. Mathematical Challenge - 40% ULO: 1, 2, 3, 4, 5, 6

Monash Online units cannot have exams. Therefore all assessment must be in-semester.

To ensure that the students work is authentic, academic staff closely supervise students' participation online and communicate with students by email regularly. They also conduct and document student interviews via the phone or online conferencing software throughout the semester. These methods complement our online assessment tools such as Respondus Lock-down browser and Turnitin.

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 applied class.
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.

Mathematics (Faculty of Science)