About Course
AI systems are increasingly used to inform decisions across sectors, and the quality of those decisions depends on how well professionals can judge AI-generated outputs and recognise the biases that shape their own interpretation of them. Building stronger capability in evaluating AI accuracy, reliability and bias gives professionals the tools to work with AI-generated outputs using sound judgement, supporting more confident and defensible AI-enabled decisions.
This course is the second in a six-part Psychology of AI series, and can be taken independently of the other five.
Learners will be equipped to evaluate AI-generated outputs, language models and AI-assisted decisions from both technical and psychological perspectives, covering accuracy, reliability, hallucination, bias and consistency alongside how human judgement can be distorted by fluency, overconfidence, anchoring, confirmation bias, automation bias and AI sycophancy.
Through hands-on exercises using Capabara, learners test and compare model outputs under different conditions, then apply what they learn to design a lightweight AI assurance protocol and communicate AI quality and risk findings to stakeholders.
Delivered through in-person classroom sessions at SIT Punggol Campus, learners can expect a combination of facilitated discussion with hands-on use of the Capabara AI Factory platform.
This course is developed in partnership with Straits Interactive, a leading edtech company committed to enabling organisations to thrive in a business landscape defined by Generative AI.
Who Should Attend
Minimum Entry Requirements
- Preferably a degree or diploma holder with at least 3 years of relevant working experience
The Psychology of AI Series
This course is part of a collection of 6 Psychology of AI courses by SITLEARN. View the full collection here.
Learning Outcomes
By the end of this course, learners will be able to:
- Explain key evaluation concepts such as precision, recall, bias metrics and hallucination rate.
- Apply critical thinking and evidence-based reasoning to interpret AI performance results.
- Conduct hands-on testing of language models using Capabara and other AI tools.
- Analyse and compare AI system outputs to detect systematic errors and biases.
- Design a lightweight AI assurance audit for ongoing organisational use.
Teaching Team
Dr. Kevin Shepherdson
Founder & CEO, Straits Interactive
Dr. Celine Chew
Chief AI Learning Officer, Straits Interactive
Course Details
Schedule
| Course Run | Dates | Time |
|---|---|---|
| January 2027 | 7 - 8 Jan | 9:00 am – 6:00 pm |
| May 2027 | 4 - 5 May | 9:00 am – 6:00 pm |
| September 2027 | 6 - 7 Sep | 9:00 am – 6:00 pm |
| January 2028 | 6 - 7 Jan | 9:00 am – 6:00 pm |
Certificate and Assessment
A Certificate of Attainment will be issued to participants who:
- Attend at least 75% of the course
- Undertake and pass non-credit bearing assessment during the course
Participants who meet the attendance requirement but do not pass the assessment will receive a Certificate of Participation.
Mode of Assessment: Assignments
Fee Structure
The full fee for this course is S$2,616.00.
| Funding Category | Eligible Funding | Course Fees Payable After Funding |
|---|---|---|
| Singapore Citizen (Below 40) | 70% | S$784.80 |
| Singapore Citizen (40 & Above) Funded under SkillsFuture Mid-Career Enhanced Subsidy (MCES) | 90% | S$304.80 |
| Singapore PR / LTVP+ Holder | 70% | S$784.80 |
| Non-Singapore Citizen | Not Eligible | S$2,616.00 |
Note: All fees above include GST. GST applies to individuals and Singapore-registered companies.
Course Runs
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