Course Summary

The Diploma in Applied Artificial Intelligence provides learners with a comprehensive foundation in computing, programming, and AI applications, designed for practical, real-world problem solving. The course emphasises logical thinking, hands-on implementation, and the integration of core technical concepts with user-focused design.

Learners begin by developing computational thinking skills and basic programming knowledge, enabling them to break down problems, design structured solutions, and implement simple programs. This is reinforced through foundational mathematics and logic, equipping learners with the analytical tools needed for algorithm development and decision-making.

The programme then advances into data structures and algorithms, where learners explore efficient ways to organise and process data. This is complemented by database application development, allowing learners to design, manage, and interact with relational databases in practical scenarios.

Building on these foundations, learners are introduced to machine learning concepts, focusing on supervised learning, data handling, and the development of simple predictive models. The emphasis is on intuitive understanding and basic implementation rather than complex theory.

Finally, the course integrates user experience and interface design principles, enabling learners to create human-centred digital solutions. Learners will design, prototype, and evaluate interfaces while considering usability, accessibility, and sustainability.

Throughout the programme, learning is highly applied, with mini projects and practical assessments that require learners to integrate multiple concepts to solve real-life problems. By the end of the course, learners will be equipped with the skills to design simple AI-driven applications, supported by strong foundations in programming, data, and user-centred design.

Course Structure

Full-Time Duration: 8 Months

Part-Time Duration: 8 Months

Delivery Mode:  Blended

Instructional Method:  

• Lecture
• Tutorial
• Discussion
• Roleplay
• Presentations
• Storytelling

Assessment Method: Project Report

Assessment Weightage: Project Report (100%)

Teacher-Student Ratio: 1:24

Graduation Requirements: Students who complete and pass the modules stipulated in the course structure and fulfil attendance requirement will be issued with a “Diploma in Applied Artificial Intelligence (AI)” by United Ceres College.

Admission Criteria

Language Requirements: 

• IELTS 5.5 or equivalent or,
• Score 70 in United Ceres College English Placement Test or,
• Completed United Ceres College Certificate in English Level 3 or Certificate in English Language

Academic Requirements: 

• Passed any 3 subjects in GCE O-Level or equivalent or,
• Completed 12 years of formal education or,
• Completed United Ceres College Certificate in General Management

Mature Applicants: 

• Candidates who are at least 30 years old with at least 8 years of working experience may apply as Mature Applicants. Applicants must submit a resume or supporting documents as proof.

Minimum Age: 17

Intake: Every month

For specific intake dates and more details, please see Academic Calendar.

Course Fee

For detailed fee information, please refer to the Course Fee Page or contact us directly.

What You Will Learn

1. Computational Thinking
This modules introduces the fundamentals of computational thinking and how it is applied in developing programming solutions to problems. Programming concepts, simple data structures and programming techniques are also covered.

2. Logic and Mathematics
This module covers logic, functions, sequence & recursion, graphic and probability. It also covers mathematical processes for developing algorithms in computing and other real-life applications, The topics include coverage of the fundamental mathematical concepts needed for computing.

3. Data Structures and Algorithms
This module introduces the fundamentals of recursion and data structures in solving problems using a programming language. Topics covered include stacks, queues and linked lists. Searching techniques and sorting algorithms are also covered.

4. Database Application Development
This module introduces the fundamental concepts of relational database systems, the design methods specific to relational database, database manipulation using a database query language, and the techniques of implementing relational databases. It will also cover implementation of simple applications to access relational database.

5. Machine Learning for Developers
This module introduces the fundamentals of machine learning principles and practices. It covers a range of machine learning models and algorithmic machine learning methods, such as supervised learning.

6. User Experience and Interface Design
This module introduces the concept of Human-Centered Design, and its practice to create useful digital products and interfaces that offer an enriching user experience (UX). The topics covered include designing sustainable interfaces, need findings, sketching and prototyping for interactive experience, and usability testing with accessibility.