Overview
Master of Science Applied Artificial Intelligence
The Applied Artificial Intelligence course provides technical and critical thinking skills in applying knowledge related to AI to real-world problems. The course aims to:
1. Develop student’s knowledge of the complex body of knowledge related to the application of the AI discipline and develop their intellectual ability for abstract analysis and synthesis at the level for postgraduate research.
2. Produce graduates who can make reasoned, critical decisions and apply AI techniques effectively to complex real world problems and derive business insight from data.
3. Equip graduates with sufficient technical and inter-personal skills to influence decision-making and strategy within an organisation through the ability to analyse the application of AI technologies.
4. Enable students to acquire cognitive and critical reflection skills to equip them for a professional career in applied AI.
5. Develop student’s appreciation of professional, ethical and legal responsibilities along with the technical skills to make an immediate contribution to their chosen professional field.
Students can choose from two distinct routes to earn their Master of Science Applied Artificial Intelligence:
| Route | Duration | Starting Month | ||||
|---|---|---|---|---|---|---|
| Full-time/Part-time | 1 year | Feb/May/Oct | ||||
Regardless if you opt for a full-time or part-time programme, all students receive the same comprehensive coverage of modules, access to lectures, and tutorial materials, ensuring that every graduate is equally prepared for the demands of a career in data science.
Structure
| Awarding authority | – | Teesside University, UK |
|---|---|---|
| Academic Year/Time Schedule/Programme Duration | – | Duration of course is 1 year |
| Mode | – | Full Time / Part Time |
| Teaching Amenities, Facilities etc | – | Lecture Rooms, Library, Computer Lab, Student Lounge |
| Intakes | – | 6 Oct 2025 23 Feb 2026 18 May 2026 26 Oct 2026 |
| Module Titles | Credits | |
|---|---|---|
| Artificial Intelligence Ethics and Applications | 20 | |
| Artificial Intelligence Foundations | 20 | |
| Big Data and Business Intelligence | 20 | |
| Deep Learning | 20 | |
| Machine Learning | 20 | |
| Software for Digital Innovation | 20 | |
| Computing Masters Project | 60 | |
Module Description
Artificial Intelligence Ethics and Applications
This module will provide students with a deep insight into the business applications of Artificial Intelligence (AI) and Data Science (DS). The module will explore a range of AI and DS applications, such as , image recognition, generative AI, autonomous machines, medical diagnosis, predictive policing, criminal justice, and fraud detection . Students will analyse both the risks and opportunities of applying AI techniques in these areas.
Artificial Intelligence Foundations
Artificial Intelligence (AI) Foundations module provides students with the foundational knowledge to study a wide range of AI applications and solutions. The module introduces knowledge representation, reasoning, problem-solving and algorithms, planning methodologies, and several AI applications.
Big Data and Business Intelligence
This module aims to develop the student’s ability to design and implement database, big data and analytics applications to meet business needs. A case study will be used to follow the system development life cycle. The student will develop a plausible application from inception to implementation for a real world scenario.
Deep Learning
Deep learning is a subset of machine learning that uses Artificial Neural Networks models with many layers to solve problems in computer vision, speech recognition, natural language process, language translation and others. The main advantage of deep learning is the ability to learn representations from raw data such as images or text without the need to hand engineer features that represent the input for the model and deliver very high accuracy. Deep learning is now the main technology behind many breakthroughs in object and voice recognition, Google Deep Mind AlphaGo, Siri (Apple), Alexa (Amazon) and Face recognition (Facebook). This module covers various deep learning methods and their practical applications. The module is assessed by in course assessment based on writing a research paper on applying deep learning techniques to a real-world data set.
Machine Learning
Machine learning is a subfield of computer science concerned with computational techniques rather than performing explicit programmed instructions. The methodology involves building a model of a given task based on observations in order to make predictions about unseen data. Such techniques are useful when the desired output is known but an algorithm is unknown, or when a system needs to adapt to unforeseen circumstances.
Software for Digital Innovation
This module provides students with an introduction to the Python programming language and its application to solving problems in Computer Science (CS),Data Science (DS), Artificial Intelligence (AI) and Financial Technology (FinTech) related to digital innovation. This involves the principles of programming, the language syntax and structure, relevant libraries and modules and how it is incorporated in existing software tools.
Computing Masters Project
This module provides students with the opportunity to undertake a major, in-depth, individual study in an aspect of computing, IT, computer science or digital technology. Normally the Masters project will be drawn from commercial, industrial or research-based problem areas. The project involves the student in researching and investigating aspects of their specific computing discipline and then producing a major deliverable (e.g. software package or tool, design, prototype, web-site, model, research findings, results of an experiment, datasets etc.). The student also carries out a critical evaluation of their major deliverable, including obtaining third party evaluation where appropriate.
Click here to view module descriptions.
For more information please refer to https://www.tees.ac.uk/
ADMISSION REQUIREMENTS
Age Requirements
- 20 years old
Academic Requirements
Normally a first degree (2.2 minimum), relevant experience or equivalent qualifications. Any first degree subject excluding BSc (Hons) Artificial Intelligence, BSc (Hons) Computer Science, and BSc (Hons) Data Science. Entry from some first degree disciplines including BSc (Hons) Computing and BSc (Hons) Information Technology depends on course content. You are required to provide a full transcript of studies to enable our admissions team to determine your eligibility.
For general information please see our overview of entry requirements.
English Requirements
- If your first language is not English, you will need an IELTS score of 6.0 equivalent with no component below 5.5
- Singapore-Cambridge GCE ‘O’ Level English – Grade C or above for all entries
- Other English requirements are per Teesside University’s entry requirement
Mature Applicants
Candidates who are at least 30 years of age with at least 8 years of working experience. To qualify as a mature candidate, you are required to submit a Personal Statement of not more than 200 words and 2 Referee Reports from at least one employer. Shortlisted applicants may be required to attend an interview.
Accreditation For Prior Learning (APL) / Credit Exemption
- Subject to University/Academic approval.
Fees
| Course Application Fee | |
|---|---|
| Course Application Fee* | Local Students: S$150 (Onetime Only) International Students: S$450 (Onetime Only) |
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Note:
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| Fees Breakdown | Total Payable | ||
|---|---|---|---|
| Local | International | ||
| Tuition Fee | S$23,500 | S$23,500 | |
| Total Course Fees Payable | S$23,500 | S$23,500 | |
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Note:
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CAREERS
Graduates of the Master of Science in Applied Artificial Intelligence at Amity Global Institute are equipped to pursue exciting roles across a wide range of industries, including finance, healthcare, retail, manufacturing, education, and the public sector. The programme’s strong focus on real-world applications ensures that students are job-ready and in demand, highlighting its relevance and impact in today’s AI-driven economy.
- AI Engineer / Machine Learning Engineer
- Deep Learning Specialist / NLP Engineer
- Data Scientist / Data Analyst / Business Intelligence Analyst
- Robotics Engineer / Intelligent Automation Consultant
- AI Software Developer / Computer Vision Engineer
- AI Research Scientist / Technology Consultant (AI)
- AI Ethics & Policy Advisor
FAQs
To apply for Master of Science Applied Artificial Intelligence in Singapore, visit the Amity Global Institute website and navigate to the “Apply Now” section.
Fill out the application forms with your details, attach any required documents, and our team will get back to you shortly regarding your application.
Yes, there is a non-refundable course application fee. This fee is exclusive of GST and covers the administrative costs of processing your application. Local students: S$150 (one time only) International students: S$450 (one time only)
You can check your application status by contacting our Singapore admissions office.
Phone: +65 6602 9500
Email: info@singapore.amity.edu
Fax: +65 6602 9509
Intake months for data science courses are in February, May, August and October. We recommend contacting our friendly and experienced programme consultant, Mr Chris, by email at cchchris@singapore.amity.edu or by Phone/WhatsApp at +65 9780 7744 to discuss the specific deadlines for each intake period, and to clarify any questions you may have.
It is advisable to apply for the Master of Science Applied Artificial Intelligence programme at least three months before the intake month to allow sufficient time for application processing, decision notification, and any necessary visa arrangements if you are an international student).
There are no differences in total payable course fees between local and international students. Both local and international students will have to pay a total course fee of S$22,000 (Excl. of GST and Non-Tuition Fees) for the MSc in Data Science.
However international students will have to pay a one-time course application fee of S$450, while local students will have to pay a one-time course application fee of S$150.