Master of Artificial Intelligence

Program Overview

The Master of Artificial Intelligence at UTS is a comprehensive program that provides students with a deep understanding of AI, data analytics, and machine learning. The program prepares graduates for careers as AI professionals, analysts, and researchers, with a focus on hands-on learning, ethics, and industry partnerships. Graduates have a high earning potential and are in high demand in various industries, including banking, healthcare, and infrastructure development.

Program Outline

Degree Overview:

• Overview:
The Master of Artificial Intelligence at UTS is a 2-year full-time or 4-year part-time program that provides students with a thorough understanding of artificial intelligence (AI), data analytics, and machine learning. The program aims to prepare graduates for careers as AI professionals, analysts, and researchers.
• Objectives:
The program's objectives are to provide students with:
• A strong foundation in the fundamental principles of AI, data analytics, and machine learning.
• The ability to apply AI techniques to solve real-world problems.
• The skills to design, develop, and deploy AI systems.
• An understanding of the ethical and societal implications of AI.
• Program Description:
The program consists of a core curriculum of courses in AI, data analytics, and machine learning, as well as a selection of elective courses. Students can choose to specialize in a particular area of AI, such as computer vision or natural language processing. The program also includes a capstone project, which gives students the opportunity to apply their skills to a real-world problem.

Outline:

• Program Content:
The program's core curriculum includes courses on:
• Foundations of AI
• Data Analytics
• Machine Learning
• Deep Learning
• Natural Language Processing
• Computer Vision
• AI Ethics
• Structure:
The program is divided into four semesters. In the first semester, students take courses in the foundations of AI, data analytics, and machine learning. In the second semester, students take courses in deep learning, natural language processing, and computer vision. In the third semester, students take courses in AI ethics and a capstone project. In the fourth semester, students take elective courses.
• Course Schedule:
The program's course schedule is as follows:
• Semester 1:
Foundations of AI, Data Analytics, Machine Learning
• Semester 2:
Deep Learning, Natural Language Processing, Computer Vision
• Semester 3:
AI Ethics, Capstone Project
• Semester 4:
Elective Courses
• Modules:
The program's modules are designed to provide students with a comprehensive understanding of AI, data analytics, and machine learning. Each module covers a specific topic area, and students are assessed on their knowledge of the material through a variety of methods, including assignments, exams, and presentations.

Assessment:

• Assessment Methods:
Students are assessed on their performance in a variety of ways, including:
• Homework assignments
• Quizzes
• Exams
• Projects
• Presentations
• Assessment Criteria:
The assessment criteria for each course vary, but generally speaking, students are assessed on their:
• Knowledge of the course material
• Ability to apply the course material to real-world problems
• Communication skills
• Teamwork skills

Teaching:

• Teaching Methods:
The program's teaching methods include:
• Lectures
• Tutorials
• Labs
• Projects
• Guest lectures
• Faculty:
The program's faculty is composed of experts in the field of AI, data analytics, and machine learning. The faculty members are actively involved in research and teaching, and they are committed to providing students with a high-quality learning experience.
• Unique Approaches:
The program's unique approaches include:
• A focus on hands-on learning.
Students are given the opportunity to apply their skills to real-world problems through projects and assignments.
• A focus on ethics.
The program includes a course on AI ethics, which helps students to understand the ethical and societal implications of AI.
• A focus on industry partnerships.
The program partners with a number of industry leaders, which provides students with opportunities to learn from and work with experts in the field.

Careers:

• Career Paths:
Graduates of the program can pursue a variety of careers in the field of AI, including:
• AI Analyst
• Machine Learning Engineer
• AI Specialist
• Computer Vision Engineer
• Natural Language Processing Engineer
• Career Opportunities:
Graduates of the program can find employment in a variety of industries, including:
• Banking and finance
• Healthcare
• Agriculture
• Infrastructure development
• Natural resource management
• Career Outcomes:
Graduates of the program are highly sought after by employers and have a high earning potential. According to the U.S. Bureau of Labor Statistics, the median annual salary for AI professionals is $126,830.