Nanyang Technological University (NTU)
Master of Computing In Applied AI (MCAAI)
50, Singapore
Master degree
DURATION
12 months
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
EARLIEST START DATE
TUITION FEES
SGD 65,400
STUDY FORMAT
On-Campus
The Master of Computing in Applied Artificial Intelligence (MCAAI), offered by the College of Computing and Data Science (CCDS), is designed to equip professionals from diverse disciplines with the knowledge and skills to effectively apply responsible AI in solving problems in their respective domains.
This programme bridges the gap between AI theory and real-world application, enabling professionals from diverse domains to integrate AI responsibly into their workflows and enhance organisational efficiency. Through a rigorous curriculum, participants will gain:
- Core foundational knowledge in AI, ensuring a deep understanding of key concepts and methodologies.
- Insights into emerging AI technologies, keeping them at the forefront of innovation.
- Hands-on experience in AI implementation, empowering them to apply AI effectively and ethically within their respective industries.
Tailored for working professionals with a Bachelor’s degree in any discipline, the MCAAI programme fosters a future-ready workforce that can navigate and harness AI advancements to accelerate AI-driven transformation across enterprises and public sector organisations in Singapore.
What Makes the MCAAI Programme Unique?
AI Where You Are – Apply AI in Your Workplace
Designed for professionals across industries, MCAAI equips you with practical AI skills to drive real impact in your organisation. Learn to integrate AI responsibly into work processes and stay ahead in the AI-powered economy.
Bring Your Problem to School – Real-World AI Solutions
Turn workplace challenges into learning opportunities with our company-sponsored capstone project. Tackle real AI problems from your organisation while receiving expert academic supervision—bridging theory, work, and career growth.
With Great Power Comes Great Responsibility – AI You Can Trust
The design and deployment of AI come with many ethical risks. MCAAI ensures graduates build responsible, transparent, and accountable AI solutions, with mandatory electives in Responsible AI practices to navigate real-world challenges.
Multiple Pathways – Upskill or Deepen AI Mastery
Whether you're new to AI or a STEM/ICT professional looking to specialise, MCAAI offers tailored learning tracks. Gain foundational AI expertise or master cutting-edge AI technologies to accelerate your career in the fast-growing AI sector.
Lead the AI revolution in your industry with MCAAI.
The MCAAI programme is designed for professionals looking to enhance their value and relevance in their current roles. Graduates will gain cutting-edge AI expertise to drive greater impact within their organisations.
For those with ICT skills, the programme provides specialised training in the latest AI technologies, enabling a seamless pivot into the rapidly growing AI sector—one of the most in-demand fields in ICT today.
Programme Structure & Duration
Duration: Full-Time – 3 Trimesters | Part-Time – 6 TrimestersStructure: 30 AUs comprising 12 AUs Core Modules and 18 AUs Elective Modules
Class Run Format
- Each 3-AU course runs over 6 weeks
- Total of 39 contact hours per course
- Weekly breakdown (6.5 hours):
- 1 hour of pre-recorded video (self-paced)
- 2 hours of mid-week hybrid lessons (6:30 pm – 8:30 pm)
- 3.5 hours Saturday in-person lesson
- Morning: 9:00 am – 12:30 pm OR
- Afternoon: 1:30 pm – 5:00 pm
- Additional hours allocated for self-study
Note: All students are required to attend both in-person classes and the mid-week hybrid session.
Curriculum
Applied AI Programming
- Learn basic Python programming using IDEs and low-code tools
- Understand the use of various AI/ML libraries
- Perform basic model training and inference
AI Algorithms Fundamentals and Application
- Understand the capabilities and limitations of different AI algorithms
- Apply and configure appropriate AI algorithms to available data and intended use cases
- Measure the performance of AI system outputs
AI UX and Data Visualisation Design Principles
- Design trust and feedback in AI user experience (UX)
- Human-centered AI interface design
- Handle different types of errors in AI systems
- Apply effective data visualisation principles and design
Best Practices in Data Governance, Preparation, and Analytics
- Design effective AI data governance strategies
- Apply data preparation principles and best practices
- Conduct data analytics that consider the limitations of data analysis techniques and datasets
Elective Courses (18 AUs)
Responsible AI Practices – Prescribed Electives
(At least two courses)
- AI ethics and governance fundamentals (2)
- Addressing issues in AI ethics and governance (3)
- Responsible generative AI and applications (3)
- Addressing issues in generative AI system design and deployment (2)
Courses can be stacked toward a graduate certificate qualification.
Domain-Focused AI Applications
- AI in banking and finance (3)
- AI in education (3)
- AI in healthcare (3)
- AI in law (3)
- AI in manufacturing (3)
- AI in marketing (3)
- AI in project management (3)
- Company-sponsored capstone project (5)
Technical AI with Applications
- Agentic AI and applications (2)
- Recommendation systems (2)
- LLM and RAG (2)
- Reinforcement learning (2)
- Transformers and generative adversarial networks (2)
- Deep learning and applications (2)
- Computer vision and applications (2)
- NLP and applications (2)
- Embedded AI and applications (2)