B.Sc Artificial Intelligence
Don't just use AI—engineer it. Build, evaluate, and responsibly deploy next-gen intelligent systems with a 4-year BSc in AI.
About This Program
Program Description
An undergraduate degree focused on the design, development and responsible use of intelligent computational systems. Students build foundations in programming, mathematics, statistics and data before progressing to machine learning, knowledge representation, deep learning, natural language processing, computer vision, generative AI and AI systems engineering. The programme emphasises not only model performance, but also data quality, evaluation, governance, safety and human impact. Practical assignments and capstone work develop the ability to transform a problem into an evidence-based AI solution and communicate its strengths, limitations and ethical implications.
Programme objectives:
• Build mathematical, statistical, programming and data foundations for AI.
• Develop competence across machine learning, deep learning, language, vision and reasoning.
• Design AI systems that can be evaluated, deployed and monitored responsibly.
• Apply governance, ethical and human-centred principles to AI decisions.
• Develop research literacy and independent problem-solving through project work.
Core Courses
- Responsible AI & Governance
- AI Systems Engineering
- Computer Vision
- Generative AI Systems
- DevOps and Cloud Deployment
- AI Product and Innovation
- Secure Software Development
Admissions
Entry Requirements
Indicative requirement — subject to institutional validation and admissions policy. Applicants should normally hold a recognised secondary-school completion qualification or an approved foundation/equivalent route, with subject preparation appropriate to the discipline. English-language thresholds, country equivalencies and any portfolio or science prerequisites must be confirmed by MIU.
What You'll Achieve
Learning Outcomes
Upon successful completion of the BSc Artificial Intelligence programme, graduates will be able to:
Apply foundational computing principles to design, develop and evaluate intelligent software systems using appropriate programming languages, algorithms and software engineering practices.
Demonstrate proficiency in mathematics, statistics and data science to analyse complex datasets and support the development of reliable artificial intelligence models.
Design, train and optimise machine learning and deep learning models to solve real-world problems across a range of application domains.
Develop AI-powered applications using techniques in natural language processing, computer vision, generative AI and knowledge representation.
Acquire, prepare and manage data through effective data collection, preprocessing, feature engineering and quality assurance techniques to support robust AI solutions.
Evaluate the performance, reliability and fairness of AI systems using appropriate metrics, validation techniques and evidence-based methodologies.
Apply responsible AI principles, including ethics, governance, transparency, accountability, privacy and safety, throughout the AI system lifecycle.
Design scalable AI systems by integrating machine learning models into software applications using modern AI engineering and deployment practices.
Identify, analyse and solve complex computational problems by selecting appropriate AI techniques, algorithms and computational methods.
Communicate technical findings effectively through professional reports, presentations and visualisations, explaining AI models, assumptions, limitations and ethical implications to both technical and non-technical audiences.
Work collaboratively in multidisciplinary teams, applying project management, leadership and professional communication skills to deliver AI-enabled solutions.
Demonstrate professional, legal and ethical responsibility in the development and deployment of artificial intelligence technologies, considering societal, environmental and regulatory impacts.
Undertake independent research and innovation by investigating emerging AI technologies, critically evaluating literature and applying research methods to novel challenges.
Plan and execute an industry-relevant capstone project that demonstrates the ability to design, implement, evaluate and document a complete artificial intelligence solution.
Demonstrate readiness for employment or postgraduate study through the application of technical, analytical, entrepreneurial and lifelong learning skills in the rapidly evolving field of artificial intelligence.
After Graduation
Career Opportunities
A Closer Look
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