Course Title: Introduction to Physical Modelling

Part A: Course Overview

Course Title: Introduction to Physical Modelling

Credit Points: 12.00


Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

PHYS1080

City Campus

Undergraduate

135H Applied Sciences

Face-to-Face

Sem 1 2006,
Sem 2 2006,
Sem 1 2007,
Sem 2 2007,
Sem 1 2008,
Sem 2 2008,
Sem 1 2009,
Sem 2 2009,
Sem 2 2011,
Sem 2 2012,
Sem 2 2013,
Sem 2 2014,
Sem 2 2015,
Sem 2 2016

PHYS1080

City Campus

Undergraduate

171H School of Science

Face-to-Face

Sem 2 2017

Course Coordinator: Associate Professor Peter Daivis

Course Coordinator Phone: +61 3 9925 3393

Course Coordinator Email: peter.daivis@rmit.edu.au


Pre-requisite Courses and Assumed Knowledge and Capabilities

None


Course Description

The aim of this course is to give students a basic introduction to applied scientific computation using a high level language. Applications include data analysis and visualization, image analysis, image manipulations and simple examples chosen from the fields of Geospatial Science and Surveying.


Objectives/Learning Outcomes/Capability Development

This course contributes to the following Program Learning Outcomes for BH116 Bachelor of Applied Science (Surveying)(Hons) and BH117 Bachelor of Applied Science (Geospatial Science)(Hons)

1.1 Describe the fundamental and applied scientific knowledge that underpins surveying and the geospatial sciences.

1.2 Demonstrate in-depth understanding of the spatial models and mathematical methods used in contemporary practice

1.3 Understand specialist bodies of knowledge in surveying and geospatial science

2.1 Apply standard and advanced techniques to solve a range of measurement and data management problems.

2.2 Proficiently perform computations in two and three dimensions.

2.3 Be proficient in the recording, storage, management and reporting of spatial information.

3.1 Design and implement creative solutions to complex problems.

3.2 Interpret and critically analyse results and make informed judgments on the appropriateness of solutions.

3.3 Apply critical and analytical skills in a scientific and professional manner.

4.1 Communicate effectively by means of oral, written and graphical presentations to peers and a wider audience  

 


After completing this course you will:

  1. have a basic knowledge of computing hardware and a programming language and its use in science
  2. be able to analyse data and solve problems using computational tools
  3. be able to use appropriate language to describe and report on the use of computational tools to analyse and solve problems

 

 

 

 


Overview of Learning Activities

Learning will occur through a series of lectures, (developing the knowledge capability dimension), computer laboratory exercises (developing the technical capability dimension) and assignments (developing the technical and communication dimensions)..

Total Study Hours

Teacher guided hours: 40

Learner directed hours: 60

 

 


Overview of Learning Resources

Lists of relevant reference texts, resources in the library and freely accessible Internet sites will be provided, along with additional materials in class. Students will also use computer equipment and software within the School for laboratory and assignment work.


Overview of Assessment

Note that:

☒This course has no hurdle requirements.

☐ All hurdle requirements for this course are indicated clearly in the assessment regime that follows, against the relevant assessment task(s) and all have been approved by the College Deputy Pro Vice-Chancellor (Learning & Teaching).

The assessments are

Practical exercises: 35% (Addresses CLOs 1, 2, 3)

On-Line tutorial tests: 15% (Addresses CLO 1)

Examination: 50% (Addresses CLOs 1, 3)