Course Title: Industrial Applications of Mathematics and Statistics 1

Part A: Course Overview

Course Title: Industrial Applications of Mathematics and Statistics 1

Credit Points: 12.00

Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

MATH2196

City Campus

Undergraduate

145H Mathematical & Geospatial Sciences

Face-to-Face

Sem 1 2010,
Sem 1 2011,
Sem 1 2012,
Sem 1 2013,
Sem 1 2014,
Sem 1 2015,
Sem 1 2016,
Sem 2 2016

MATH2196

City Campus

Undergraduate

171H School of Science

Face-to-Face

Sem 2 2017,
Sem 1 2018,
Sem 2 2018,
Summer2019,
Sem 1 2019,
Sem 2 2019,
Sem 1 2020,
Sem 2 2020,
Sem 1 2021,
Sem 2 2021,
Sem 1 2022,
Sem 2 2023

Course Coordinator: Professor Asha Rao

Course Coordinator Phone: +61399251843

Course Coordinator Email: asha.rao@rmit.edu.au

Course Coordinator Availability: By appointment, by email


Pre-requisite Courses and Assumed Knowledge and Capabilities

Assumed Knowledge 

This is the first of the capstone courses for the Applied Mathematics and Statistics degree and the Mathematics and Statistics double major in the Applied Sciences degree. You are expected to have completed at least 12 courses or be in the final year of your program. The prerequisite capabilities are those from core courses undertaken in the preceding years of your program stream, or evidence of equivalent capabilities.

 


Course Description

You will participate in a simulated Work Integrated Learning experience, applying your mathematical and statistical knowledge and skills to solve real-world problems, and will be assessed in a simulated workplace context.

A wide variety of contemporary industry experts will discuss their carer trajectories, who will speak about their application of mathematics and statistics in their workplace, or the need for mathematical and statistical experts within their industry. 


This course will enable career development and build your capability around information literacy. In particular, this course will enable you to:

  • Apply the knowledge and skills obtained to search for internships and jobs;
  • Interpret and apply mathematical and statistical concepts in a variety of contexts;
  • Develop your verbal and written communication skills, your ability to work in teams, respect timelines, and adhere to professional ethics.

This course prepares you for industry placement or a project with industry, in MATH2197 Industrial Applications in Mathematics and Statistics 2. 


Objectives/Learning Outcomes/Capability Development

This course contributes to the following Program Learning Outcomes for BP083 Bachelor of Applied Mathematics and Statistics:

PLO1: Apply a broad and coherent knowledge of mathematical and statistical theories, principles, concepts and practices with multi-disciplinary collaboration.  


PLO2: Analyse and critically examine the validity of mathematical and statistical arguments and evidence using methods, technical skills, tools and computational technologies. 


PLO3: Formulate and model real world problems using principles of mathematical and statistical inquiry to inform evidence-based decision making.  


PLO4: Critically evaluate and communicate technical and non-technical mathematical and statistical knowledge to diverse audiences utilising a variety of formats employing culturally safe practices.  


PLO5: Work ethically and independently, with integrity and accountability to develop professional agility for future careers.  


PLO6: Collaborate and contribute within diverse, multi-disciplinary teams, with commitment to diversity, equity and globally inclusive perspectives and practices including First Nations knowledges.


Upon successful completion of this course you should be able to:

 

  1. 1. Apply technical knowledge and problem solving ability to real-world problems.
    2. Access data and information and evaluate its quality through practical application.
    3. Demonstrate reflective learning through professional experience and collaboration.
    4. Report project findings in both written and oral form, integrating feedback from all relevant stakeholders.
    5. Describe the impact and influence of ethical considerations in the practice of mathematics and statistics.
    6. Apply professional behaviours and practices to a small project team, including understanding the dynamics of a small team, managing your time and scheduling your activities.


Overview of Learning Activities

Weekly workshops will build upon your skills in written communication, oral communication, project management, teamwork, and career planning. 

Industry-relevant mathematics and statistics job opportunities will be explored through a mixture of discussion with industry guests, and in-class discussion of published resources. 

As a group you will demonstrate ability to solve real world problems using the knowledge and competencies acquired during your program by proposing solutions to problems in national and international mathematics competitions.


Overview of Learning Resources

RMIT will provide you with resources and tools for learning in this course through myRMIT Studies Course Site. Canvas will be used to give access to general supporting material (readings, videos, web link) and to discussion forums. 

The library, on-line resources and/or specific material given by the teaching team will provide you additional information necessary to the completion of your project or task. There are academic referencing, study support, subject specialist help and Library guides available to support your learning. For further information, please visit the Library page on the RMIT University website and the myRMIT student portal. 

For each specific subject you might find additional material athttp://rmit.libguides.com/mathstats and http://rmit.libguides.com/compsci


Overview of Assessment

This course has no hurdle requirements. 

Assessment Tasks: 

Assessment Task 1: Industry Awareness Briefing Notes
Weighting 30%
This assessment supports CLOs 2 & 3

Assessment Task 2: Micro-credentials 
Weighting 10%
This assessment supports CLOs 1 & 4

Assessment Task 3: Mock Job Application
Weighting 20%
This assessment supports CLOs 1, 2, 3 & 4

Assessment Task 4: Problem Solving Group Presentation and Peer Review
Weighting 40%
This assessment supports CLOs 1, 2, 3, 4, 5 & 6