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WSQ - Core Principles and Ethical Challenges in Generative AI

Sessions 1 day
Duration 8 hrs
Level Beginner
Assessment 1 hr

Venue

12 Woodlands Square #07-85/86/87 Woods Square Tower 1, Singapore 737715. 5 mins walk from Woodlands (NS9) MRT station.

The venue is disabled-friendly.

TSC Title: : Generative AI Principles and Applications
TSC Code: ICT-INT-0052-1.1

By end of the course, learners should be able to:

LO1: Demonstrate generative AI concepts and applications relevant to customer service and hospitality management.
LO2: Apply prompt engineering techniques and analyse output variations to improve generative AI performance in service settings.
LO3: Identify ethical risks and analyse bias in AI-generated content used in customer engagement.

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Certificate of Completion from Tertiary Courses - Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Completion from Tertiary Courses.
OpenCerts from SkillsFuture Singapore - After passing the assessment(s) and achieving at least 75% attendance, participants will receive a OpenCert (aka Statement of Achievement) from SkillsFuture Singapore, certifying that they have achieved the Competency Standard(s) in the above Skills Framework.

WSQ - Core Principles and Ethical Challenges in Generative AI

Course Code: TGS-2025060473

WSQ
SkillsFuture Credit
PSEA
UTAP
SFEC
Absentee Payroll
MCES

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WSQ Core Principles and Ethical Challenges in Generative AI introduces learners to the foundational principles of generative AI and its real-world applications, particularly in customer service and hospitality management. Participants will explore the core concepts and model types, including the distinctions between generative and discriminative models. The course features practical demonstrations of generative AI tools used in summarisation, reasoning, and content transformation.

Learners will also develop prompt engineering skills, analysing the impact of prompt structure on AI output quality and model performance. Ethical considerations form a key part of the course, with a focus on understanding bias in AI-generated content, examining training data limitations, and evaluating the societal implications of AI use. By the end of the course, participants will be able to apply AI responsibly in service environments while maintaining ethical and inclusive standards in customer engagement.

Full Fee $500.00 Before GST

GST $45.00 9% of fee

Baseline Nett $295.00 SG/PR age 21+ · 50% funded

MCES / SME Nett $195.00 SG age 40+ · 70% funded

SkillsFuture Enterprise Credit (SFEC)

Eligible Singapore-registered companies can tap on $10000 SFEC to cover out-of-pocket expenses.Click here to submit SkillsFuture Enterprise Credit

SkillsFuture Credit (SFC)

Eligible Singapore Citizens can use their SFC to offset course fee payable after funding but the $4,000 Additional SFC (Mid-Career Support) cannot be used. Click here for SkillsFuture Credit submission

UTAP

Eligible NTUC members can apply for 50% of the unfunded fee from UTAP, capped up to $250/year and for members aged 40 and above, capped up to $500/year. Click here to submit UTAP

PSEA

Eligible Singapore Citizens can use their PSEA funds to offset course fee payable after funding.

To check for Post-Secondary Education Account (PSEA) eligibility for this course, Visit SkillsFuture (course code: TGS-2025060552)

Scroll down to “Keyword Tags” to verify for PSEA eligibility.
If there is “PSEA” under keyword tags, the course is eligible for PSEA.

Once you are eligible for PSEA, please download and fill up the PSEA Withdrawal Form and email to us.

Please bring your own laptop for hands-on training. If you don't have laptop, we can provide spare laptop for training use.

We provide free consultation related to the subject matter after the course.
Please email your queries to enquiry@tertiaryinfotech.com and we will forward your queries to the subject matter experts.

You can register your interest without upfront payment. There is no penalty for withdrawal of the course before the class commences.
We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% for any paid amount.
Note the venue of the training is subject to changes due to availability of the classroom.

Course Details

LU1: Generative AI Fundamentals

T1: Underlying principles, core concepts and theories governing generative AI

T2: Difference between generative and discriminative models

T3: Demonstrate the use of generation AI in diverse applications (e.g., summarisation, inference, reasoning, transformation of content, augmentation of content)

LU2: Prompt Engineering

T1: Importance of data quality, preprocessing, model pipeline and model training (e.g., impact of data bias from training data)

T2: Impact of prompt engineering on the model outputs of generative AI

T3: Apply understanding of generative AI principles to use cases

T4: Analyse generative AI models' performance metrics and evaluate the influence of prompt variations

LU3: Ethical Considerations

T1: Generative AI model workings, including training data, algorithms, and outputs

T2: Identify the ethical implications and societal impact of AI-generated content

T3: Analyse limitations and potential biases in AI-generated content

Written Exam
Practical Exam

Course Info

Promotion Code

Your will get 10% discount voucher for 2nd course onwards if you write us a Google review.

Minimum Entry Requirement

Knowledge and Skills

Able to operate using computer functions
Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)

Attitude

Positive Learning Attitude
Enthusiastic Learner

Experience

Minimum of 1 year of working experience.

Target Age Group: 18-65 years old

Minimum Software/Hardware Requirement

Software:

TBD

Hardware: Window or Mac Laptops

Job Roles

Customer Experience Manager
Digital Transformation Executive
AI Support Specialist
Service Quality Analyst
Marketing Executive
Hospitality Manager
Contact Centre Supervisor
Customer Insights Analyst
Business Process Analyst
Operations Coordinator
Digital Innovation Officer
Prompt Engineer
Data Ethics Consultant
AI Trainer
Learning & Development Specialist
Frontline Team Lead
Customer Support Executive
User Experience Designer
Corporate Trainer (AI Tools)
AI Adoption Consultant

Trainers

Dwight Nuwan Fonseka

Dwight Nuwan Fonseka is Head of Data Science at Plano Pte. Ltd. and an ACLP-certified trainer with deep expertise in data analytics, machine learning, and AI applications. He has extensive hands-on experience developing predictive models, RShiny dashboards, and deep learning solutions using R, Python, TensorFlow, and Keras. With a strong professional background in healthcare, finance, and customer analytics, Dwight brings an applied perspective to teaching AI, focusing on both the opportunities and risks of emerging technologies.