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Master of Data Science (Artificial Intelligence Specialisation)

Provider:
Sydney Polytechnic Institute
Course Code:
MDS-AI
CRICOS Code:
112062K
Qualification Level:
Masters
Course Area:
Information System, Information Technology
Duration:
2-Year
Study Mode:
Full Time
Location:
Haymarket, New South Wales, Australia
Course Fees:
AUD 52,800 Per Course
Delivery Mode:
On Campus
Target:
International
Intake:
March, July, October
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Course Overview

The Master of Data Science (MDS) provides students with comprehensive mastery of all aspects of knowledge and skills related to data science and an opportunity to focus on specialised technical, theoretical or managerial skills through the choice of one specialisation. The MDS places an emphasis on professional practice, effective communication, and project management using technical and non-technical approaches. Students will acquire extensive and deep knowledge to enable them to successfully design, implement and manage data science based solutions in complex real-world applications. Students will become confident in utilising the latest technologies in the data science, significantly enhancing their prospects in career development or entrepreneurship.
Students can nominate a specialisation that allows them to fulfil their own particular interests, their own industry needs, or their own career goals. In particular, students may choose to gain expertise in Artificial Intelligence if they choose not to proceed with the default specialisation.
The MDS is designed for students who have limited experience in, or have been seeking a qualification in, data science. The degree also caters for candidates who already have a sound data science background but wish to update and develop their knowledge and skills to keep pace with the rapid changes in technology and the business opportunities related to the latest advances in data science.

Course Structure

To qualify for the award of the Master of Data Science, a candidate must complete the following:

Common Core Units

  1. MDS601 Programming Foundations for Data Science 
  2. MDS602 Mathematical Foundations 
  3. MDS603 Data Science Methodology 
  4. MDS604 Database Systems and Infrastructure 
  5. MDS605 Machine Learning and Data Mining 
  6. MDS606 Data Science Research and Ethics 
  7. MDS607 Artificial Intelligence and Innovation 
  8. MDS608 Professional Practice 
  9. MDS650 Data Science Capstone Project; or MDS651 Industrial Experience Project

Specialisation Core Units

  1. MDS613 Deep Learning 
  2. MDS616 Reinforcement Learning 
  3. MDS620 Probabilistic Artificial Intelligence 

Elective Units - [Any Two]

  1. MDS609 Business Intelligence and Analytics 
  2. MDS610 Decision Making for Analytics 
  3. MDS614 Unstructured Data and Computer Vision 
  4. MDS617 Mixed Reality 
  5. MDS618 Autonomous Theory and Programming Robots 
  6. MDS619 Natural Language Processing and Applications 
  7. MDS621 Game Designing 
  8. MDS622 Foundations and Applications of Fin-Tech 

Entry Requirement

Admission Requirements
Academic Entry Requirements

Direct Entry to this course requires one of the following:

  • Completion of an AQF Level 7 qualification such as an approved three-year undergraduate degree which includes some study areas requiring quantitative reasoning and analysis with a GPA of 4.5 or above or;
  • Completion of the SPI Graduate Diploma of Data Science or SPI Graduate Certificate in Data Science. or;
  • Other qualifications with the combination of education and relevant work or other experience will be considered on a case-by-case basis. 
Language Requirement
IELTS Score (Minimum) IELTS Academic - A minimum result of 6.5 overall and a minimum result of 6.0 in each subtest; or an equivalent score.

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