Want to master the application of artificial intelligence (AI) and data skills? NYP’s Diploma in AI & Data Engineering provides learners with fundamental competencies in engineering, AI, and data management and analysis. Graduates can anticipate opportunities to develop and deploy AI solutions across critical sectors, including electronics, aerospace, advanced manufacturing, biomedical, and urban solutions.

Applicants should demonstrate:

• Interest in applying AI and data analysis skills in engineering applications;
• Experience in a school environment (e.g. through a CCA, a community activity or a class leadership position) where you learned about various computer technologies, including coding or networks, or in an external context (e.g. AI, data analytics, robotics/automation technology applications events or online learning sites for AI, Internet of Things (IoT) topics); and,
• Leadership, teamwork and critical thinking skills to develop innovative and creative solutions in the AI, data, robotics or IoT domains

Interview

If you are shortlisted, you will be invited for an interview to share more about your passion for the course with a panel of interviewers. You will be assessed on your interest, aptitude, as well as your achievements in both AI and non-AI domains. The duration of the interview will be between 15 to 25 minutes for a one-to-one interview, or longer if it is a group interview. 

Some questions which you may be asked during the interview include:

• What made you realise that you wanted to have a career in AI & Data Engineering?
• Have you tried coding & AI? How was your experience?
• What motivates you to have a career in AI and Data Engineering?
• Have you taken part in any competitions/CCAs that are AI-related?
• Do you have any experience in data processing?

Portfolio (Optional)

You should include in your portfolio, any evidence and/or activities (e.g. AI or robotics/automation/IoT applications competitions) that showcase your character and involvement relevant to AI or Data Engineering (such as leadership skills or coding skills).

Examples of what to include in your portfolio:

• Testimonials
• Certificates (e.g. academic, achievement and/or personal development)
• Awards or participation in AI & Data Engineering-related competitions, at school and/or national level
• Evidence of AI or Robotic/Automation projects, (e.g. coursework or CCA)
• Relevant learning journeys or Applied Learning Module (ApLM, formerly known as Advanced Elective Modules [AEM])
• Evidence of leadership activities or roles
• Participation in CCAs