Course Title: Digital Technologies
Part A: Course Overview
Course Title: Digital Technologies
Credit Points: 12.00
Flexible Terms
Course Code |
Campus |
Career |
School |
Learning Mode |
Teaching Period(s) |
INTE2624 |
City Campus |
Research |
175H Computing Technologies |
Internet |
RSCHYr2023 (All) |
Course Coordinator: Jenny Zhang
Course Coordinator Phone: +61 3 9925 2774
Course Coordinator Email: xiuzhen.zhang@rmit.edu.au
Course Coordinator Location: By appointment
Course Coordinator Availability: By appointment
Pre-requisite Courses and Assumed Knowledge and Capabilities
You must be enrolled in a PhD or Master by Research program at RMIT to take this course.
You should have basic level of programming and computing literacy.
Course Description
Our current digital world is full of data and information in large volumes and various forms. Digital computing technologies are essential for developing data-driven solutions to challenging scientific research questions from all scientific disciplines, ranging from physical sciences and engineering to social sciences.
This course aims to introduce digital technologies and particularly build programming, data science and Artificial Intelligence capabilities for HDR candidates to support your research project.
The course incorporates both cross-disciplinary and disciplinary specific contents.
Topics to cover include:
- Scientific programming
- Scientific data processing
- Artificial Intelligence and machine learning
Objectives/Learning Outcomes/Capability Development
On successful completion of the course, you will be able to:
- Design efficient algorithmic solutions using a programming language for computing problems.
- Process, clean and transform large volumes of data in various forms.
- Apply principles and algorithms of Artificial Intelligence and machine learning for predictive data analytics.
- Critically evaluate and synthesise AI and machine learning solutions for a range of problem settings.
Overview of Learning Activities
You will participate in a range of learning activities, which may include self-directed online learning, expert facilitated seminars and workshops, participation in disciplinary and cross-disciplinary peer discussion and peer assessment.
Overview of Learning Resources
RMIT will provide you with resources and tools for learning in this course through our online systems.
Lists of learning resources will be provided during the course, and you will be expected to build on these through your own literature searches.
There are services available to support your learning through the University Library. The Library provides guides on academic referencing and subject specialist help as well as a range of study support services. For further information, please visit the Library page on the RMIT University website and the myRMIT student portal.
Overview of Assessment
You will be assessed on how well you meet the course’s learning outcomes. Assessment tasks may include:
- The implementation of a software solution to a data analysis problem in your research area.
You will be required to demonstrate your knowledge in digital technologies through the application of a software package and programming language to a data analysis problem in your research area.
If you have a long-term medical condition and/or disability it may be possible to negotiate to vary aspects of the learning or assessment methods. You can contact the program coordinator or the Equitable Learning Services team if you would like to find out more.
Your course assessment conforms to RMIT assessment principles, regulations, policies and procedures.