MC271 - Master of Artificial Intelligence

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Plan: MC271VRI - Master of Artificial Intelligence
Campus: RMIT University Vietnam

Program delivery and structure

Approach to learning and assessment
Work integrated learning
Program structure

Approach to learning and assessment

Your learning experiences will involve a broad mix of study modes, including lectures, tutorials, practical classes, studios, project work and seminars, using face-to-face, online, intensive, and other flexible delivery mechanisms.

Assessment is designed to give you opportunities to demonstrate your capabilities. You will find that the forms of assessment used may be different for each course, depending on the course objectives and learning outcomes.

Your assessment in this program will include all or some of the following:

  • Timed Assessments: an individual form of assessment where you are asked to demonstrate your ability to explain principles and to solve problems;
  • Assignments and projects: some will require you to demonstrate an ability to work alone, while some will involve group work requiring you to be part of team with other students;
  • Reflective journals: where you pause to consider what you have learnt and reflect on the further development of the related capability;
  • Assessed tutorials or presentations: a form of in-class test which you will be required to complete either individually or as a team:
  • Self-assessment and peer-assessment: for assessment activities such as seminars you may be asked to assess your own work, the work of your group, or the work of other groups. This is part of equipping you to become more independent in your own learning and to develop your assessment skills.

Assessments you complete will enable the teaching staff to provide you with feedback on your progress. This will enable you to improve your performance in the future.

If you are living with disability, long-term illness and/or a mental health condition, we can support you by making adjustments to activities in your program so that you can participate fully in your studies. To receive learning adjustments, you need to register with Equitable Learning Service https://www.rmit.edu.au/students/support-and-facilities/student-support/equitable-learning-services

The University considers the wellbeing and safety of all students, staff and the community to be a priority in on-campus learning and professional experience settings.

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Work integrated learning

RMIT is committed to providing students with an education that strongly links formal learning with workplace experience. As a student enrolled in an RMIT program you will:

  • undertake and be assessed on a structured activity that allows you to learn, apply and demonstrate your professional or vocational practice
  • interact with industry and community when undertaking this activity
  • complete an activity in a work context or situation that may include teamwork with other students from different disciplines.
  • underpin your learning with feedback from interactions and contexts distinctive to workplace experiences.

In this program, you will be doing specific courses (COSC3003 Artificial Intelligence Postgraduate Project in the project stream or COSC2993 Minor Thesis/Project in the research stream) that focus on work integrated learning (WIL). You will be assessed on professional work in a work place setting and receive feedback from those involved in your industry. Any or all of these aspects of a WIL experience may be in a simulated workplace learning environment.

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Program Structure

To graduate you must complete the following. All courses listed may not be available each semester.
 

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Year One of Program

Complete the following Six (6) courses:

Course Title

Credit Points

Course Code

Campus

Programming Fundamentals 12 COSC2976 RMIT University Vietnam
Discrete Mathematics 12 MATH2448 RMIT University Vietnam
The AI Professional 12 COSC3005 RMIT University Vietnam
Practical Data Science with Python 12 COSC2999 RMIT University Vietnam
Artificial Intelligence 12 COSC2986 RMIT University Vietnam
Algorithms and Analysis 12 COSC2203 RMIT University Vietnam
AND
Select and Complete Two (2) Courses from the Program Options List: Please refer to the list of Program Option Courses at the end of the program structure.
 
AND

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Year Two of Program

Complete the following four (4) courses:

Course Title

Credit Points

Course Code

Campus

Intelligent Decision Making 12 COSC3009 RMIT University Vietnam
Programming Autonomous Robots 12 COSC3011 RMIT University Vietnam
Deep Learning 12 COSC3007 RMIT University Vietnam
Computational Machine Learning 12 COSC3013 RMIT University Vietnam
 
AND

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Project/Research Options

{
Project Option: Complete the following One (1) course:

Course Title

Credit Points

Course Code

Campus

Artificial Intelligence Postgraduate Project 24 COSC3003 RMIT University Vietnam
AND
Select and Complete Two (2) Courses from the Program Options List. Please refer to the list of Program Option Courses at the end of the program structure.
}
OR
Research Option: Complete the following Two (2) Courses:

Course Title

Credit Points

Course Code

Campus

Research Methods 12 COSC2991 RMIT University Vietnam
Minor Thesis/Project 36 COSC2993 RMIT University Vietnam
 
AND

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Program Options

Program Options List

Course Title

Credit Points

Course Code

Campus

Advanced Programming for Data Science 12 COSC3015 RMIT University Vietnam
Data Mining 12 COSC2989 RMIT University Vietnam
Social Media and Networks Analytics 12 COSC2984 RMIT University Vietnam
Games and Artificial Intelligence Techniques 12 COSC2997 RMIT University Vietnam
Mixed Reality 12 COSC2995 RMIT University Vietnam
Cloud Computing 12 COSC2980 RMIT University Vietnam
Programming Internet of Things 12 COSC3001 RMIT University Vietnam
 

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