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WSQ - AWS Certified AI Practitioner Training

Course Information

  • Sessions 2 days
  • Duration 16 hrs
  • Level Beginner
  • Assessment 2 hrs

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.

Skills Framework

TSC Title
Artificial Intelligence Application in Product Development
TSC Code
ICT-TEM-3034-1.1

Funding Validity

Funding for this course is valid from 23 Sep 2024 to 22 Sep 2026. Register and complete the course within this period to qualify for funding support.

Learning Outcomes

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

  • LO1: Implement AI applications with Amazon Q business and AWS AI models.
  • LO2: Deploy AWS AI Bedrock workflows according to plan and machine learning techniques.
  • LO3: Identify and report issues with AI applications and data and implementation procedures.
  • LO4: Maintain data interoperability during AI development in accordance to principles of data management.
  • LO5: Perform data cleaning techniques to optimize AWS Foundation models.

Course Brochure

Download Course Brochure

Certification

  • Certificate of Achievement from Tertiary Infotech Academy Pte Ltd - Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Achievement from Tertiary Infotech Academy Pte Ltd.
  • 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 - AWS Certified AI Practitioner Training

Course Code: TGS-2024049338
  • WSQ
  • SFC
  • PSEA
  • UTAP
  • SFEC
  • Absentee Payroll
  • MCES

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What's This Course About

This WSQ AWS Certified AI Practitioner Training provides learners with a comprehensive foundation in AI and machine learning using AWS technologies. Participants will explore fundamental AI concepts, machine learning workflows, and generative AI capabilities to develop AI-driven applications. The course covers AWS AI services, including Amazon Q and AWS AI Bedrock, enabling learners to deploy and optimize foundation models effectively. Emphasis is placed on data management, interoperability, and implementing best practices for AI development within an AWS ecosystem.

Through hands-on learning, participants will apply AI security, compliance, and governance frameworks to ensure ethical and responsible AI deployment. The course also covers prompt engineering, model fine-tuning, and performance evaluation to enhance AI system efficiency. By the end of this training, learners will be equipped with the skills to design, implement, and maintain AI applications using AWS, preparing them for AWS AI certification and real-world AI solution deployment.

Bonus: Free Practice Exams

Get exam-ready on our Practice Exam Portal — train in realistic Practice Mode and timed Exam Mode, then retake them as many times as you like before the real exam.

Start Practising →

WSQ Funding

Full Fee $900.00 Before GST
GST $81.00 9% of fee
Baseline Nett $531.00 SG/PR age 21+ · 50% funded
MCES / SME Nett $351.00 SG age 40+ · 70% funded
SkillsFuture Enterprise Credit (SFEC)

Eligible Singapore-registered companies can tap on $10000 SFEC to cover out-of-pocket expenses.

View on SkillsFuture for Business

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.

Direct Application on SkillsFuture Portal

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.

Submit UTAP Claim

PSEA

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

Check PSEA Eligibility

  • 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, then submit the completed form to us:

PSEA Withdrawal FormSubmit PSEA Form

Course FeeBefore Funding

$900.00 (GST-exclusive)
$981.00 (GST-inclusive)

Course Date

* Required Fields

Additional Note

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

Post-Course Support

  • 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.

Cancellation & Reschedule Policy

  • 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

Course Details

What You'll Learn

Topic 1 : Fundamentals of AI and ML

Basic AI concepts and terminologies

Practical use cases for AI

Machine Learning development lifecycle

Topic 2: Fundamentals of Generative AI

Basic concepts of generative AI.

Capabilities and limitations of generative AI for solving business problems

AWS infrastructure and technologies for building generative AI applications

Topic 3: Applications of Foundation Models

Design considerations for applications that use foundation models

Effective prompt engineering techniques

Training and fine-tuning process for foundation models

Methods to evaluate foundation model performance

Amazon Q

Topic 4: Guidelines for Responsible AI

Development of AI systems that are responsible.

Importance of transparent and explainable models.

Topic 5: Security, Compliance, and Governance for AI Solutions

Methods to secure AI systems.

Governance and compliance regulations for AI systems.

Assessment

  • Written Exam
  • Practical Exam

Course Info

Promotion Code

Promo or discount cannot be applied to WSQ courses

Minimum Entry Requirement

Knowledge and Skills

  • Able to operate using computer functions with minimum Computer Literacy Level 2 based on ICAS Computer Skills Assessment Framework
  • 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 Year Group : 21-65 years old

Minimum Software/Hardware Requirement

Software:

You will need a AWS account (Credit Card is required).

Hardware: Windows and Mac Laptops

About Progressive Wage Model (PWM)

The Progressive Wage Model (PWM) helps to increase wages of workers through upgrading skills and improving productivity. 

Employers must ensure that their Singapore citizen and PR workers meet the PWM training requirements of attaining at least 1 Workforce Skills Qualification (WSQ) Statement of Attainment, out of the list of approved WSQ training modules.

For more information on PWM, please visit MOM site.

Funding Eligility Criteria

Individual Sponsored Trainee Employer Sponsored Trainee
  • Singapore Citizens or Singapore Permanent Residents
  • From 1 October 2023, attendance-taking for SWDA's (formerly SSG) funded courses must be done digitally via the Singpass App. This applies to both physical and synchronous e-learning courses.​
  • Trainee must pass all prescribed tests / assessments and attain 100% competency.
  • We reserves the right to claw back the funded amount from trainee if he/she did not meet the eligibility criteria.
  • Singapore Citizens or Singapore Permanent Residents who are DIRECT EMPLOYEE of the sponsoring company.
  • From 1 October 2023, attendance-taking for SWDA's (formerly SSG) funded courses must be done digitally via the Singpass App. This applies to both physical and synchronous e-learning courses.​
  • Trainee must pass all prescribed tests / assessments and attain 100% competency.
  • We reserves the right to claw back the funded amount from the employer if trainee did not meet the eligibility criteria.

 SkillsFuture Credit: 

  • Eligible Singapore Citizens can use their SkillsFuture Credit to offset course fee payable after funding.

 PSEA:

  • To check for Post-Secondary Education Account (PSEA) eligibility, goto mySkillsFuture portal and search for this course code.
  • Scroll down to "Keyword Tags" to verify for PSEA eligibility.
  • If there is “PSEA” under keyword tags, the course is eligible for PSEA.  
  • And if there is no “PSEA” under keyword tags, the course is ineligible for PSEA. 
  • Not all courses are eligible for PSEA funding.

 Absentee Payroll (AP) Funding: 

  • $4.50 per hour, capped at $100,000 per enterprise per calendar year.
  • AP funding will be computed based on the actual number of training hours attended by the trainee.

 SFEC:

  • If the Training Provider has submitted an enrolment for course fee grant claim in Training Partners Gateway (TPGateway), SWDA would be able to derive SFEC funding based on this record. There is no need for enterprise to submit any claim request and the SFEC claim will be automatically generated and disbursed.
  • Where there is no such record, eligible employers are required to submit an SFEC claim after course completion via the SFEC microsite.
  • SkillsFuture Enterprise Credit (SFEC) Microsite 

 

Steps to Apply Skills Future Claim

  • The staff will send you an invoice with the fee breakdown.
  • Login to the MySkillsFuture portal, select the course you’re enrolling on and enter the course date and schedule.
  • Enter the course fee payable by you (including GST) and enter the amount of credit to claim.
  • Upload your invoice and click ‘Submit’

SkillsFuture Level-Up Program

The  SkillsFuture Level-Up Programme provides greater structural support for mid-career Singaporeans aged 40 years and above to pursue a substantive skills reboot and stay relevant in a changing economy. For more information, visit SkillsFuture Level-Up Programme

Get Additional Course Fee Support Up to $500 under UTAP

The Union Training Assistance Programme (UTAP) is a training benefit provided to NTUC Union Members with an objective of encouraging them to upgrade with skills training. It is provided to minimize the training cost. If you are a NTUC Union Member then you can get 50% funding (capped at $500 per year) under Union Training Assistance Programme (UTAP).

For more information visit NTUC U Portal – Union Training Assistance Program (UTAP)

Steps to Apply UTAP

  • Log in to your U Portal account to submit your UTAP application upon completion of the course.

Note

  • SWDA subsidy is available for Singapore Citizens, Permanent Residents, and Corporates.
  • All Singaporeans aged 25 and above can use their SkillsFuture Credit to pay. For more details, visit www.skillsfuture.gov.sg/credit
  • An unfunded course fee can be claimed via SkillsFuture Credit or paid in cash.
  • UTAP funding for NTUC Union Members is capped at $250 for 39 years and below and at $500 for 40 years and above.
  • UTAP support amount will be paid to training provider first and claimed after end of class by learner.

Appeal Process

  1. The candidate has the right to disagree with the assessment decision made by the assessor.
  2. When giving feedback to the candidate, the assessor must check with the candidate if he agrees with the assessment outcome.
  3. If the candidate agrees with the assessment outcome, the assessor & the candidate must sign the Assessment Summary Record.
  4. If the candidate disagrees with the assessment outcome, he/she should not sign in the Assessment Summary Record.
  5. If the candidate intends to appeal the decision, he/she should first discuss the matter with the assessor/assessment manager.
  6. If the candidate is still not satisfied with the decision, the candidate must notify the assessor of the decision to appeal. The assessor will reflect the candidate’s intention in the Feedback Section of the Assessment Summary Record.
  7. The assessor will notify the assessor manager about the candidate’s intention to lodge an appeal.
  8. The candidate must lodge the appeal within 7 days, giving reasons for appeal 
  9. The assessor can help the candidate with writing and lodging the appeal.
  10. he assessment manager will collect information from the candidate & assessor and give a final decision.
  11. A record of the appeal and any subsequent actions and findings will be made.
  12. An Assessment Appeal Panel will be formed to review and give a decision.
  13. The outcome of the appeal will be made known to the candidate within 2 weeks from the date the appeal was lodged.
  14. The decision of the Assessment Appeal Panel is final and no further appeal will be entertained.
  15. Please click the link below to fill up the Candidates Appeal Form.

Job Roles

Job Roles

  • AI Practitioner
  • Machine Learning Engineer
  • Data Scientist
  • AI Developer
  • Cloud AI Specialist
  • AI Solutions Architect
  • Data Engineer
  • AI Consultant
  • AI Research Scientist
  • AWS Cloud Engineer
  • Business Intelligence Developer
  • AI Product Manager
  • AI Analyst
  • Machine Learning Operations (MLOps) Engineer
  • Data Analyst
  • Cloud Solutions Architect
  • Software Engineer
  • Technical Program Manager
  • IT Project Manager
  • Systems Architect

Trainers

Trainers

CY Quah is an ACLP-certified trainer and data science professional with extensive experience in Python, NLP, and machine learning. He has led AI training programs for SAP, Temasek Polytechnic, and IMDA under the SGUnited Mid-Career Pathways initiative, and has delivered corporate workshops on text analytics, recommender systems, and chatbot development. His expertise includes applying NLP tools such as NLTK, spaCy, and Gensim for sentiment analysis, topic modeling, and text classification.
Amin Mahetar is a cloud and DevOps engineer with over 15 years of experience in IT infrastructure, automation, and cloud solutions across AWS and Microsoft Azure environments. A Microsoft Certified Trainer (MCT) and Azure Administrator Associate, he has implemented and managed enterprise-scale cloud deployments across industries including finance, logistics, and manufacturing. His areas of expertise include virtualization, networking, identity management, and automation using PowerShell and Azure CLI. Known for his structured and hands-on training style, Amin has guided numerous professionals in achieving their Azure certifications and advancing their cloud careers.

Mohan Pothula is a data engineering and AI systems specialist with over 18 years of experience in cloud architecture, automation, and data-driven innovation. He has delivered enterprise solutions for organizations such as DBS Bank and SPH Media, focusing on AI integration, DevOps, and analytics pipeline optimization. Mohan holds certifications in AWS, Kubernetes, and Cloud DevOps, and is well-versed in operationalizing AI models within cloud environments. His structured teaching style enables learners to understand and apply AI technologies effectively in production contexts.
In this course, Mohan focuses on guiding learners through the core concepts of AI, machine learning, and cloud-based automation within the AWS ecosystem. His sessions cover data preparation, model deployment, and AI ethics, blending theory with hands-on application. Participants gain the confidence to use AWS AI services effectively, enabling them to support business innovation and intelligent automation initiatives.

Agus Salim is an experienced IT solutions and cybersecurity professional with a strong foundation in cloud infrastructure and project management. With over a decade of experience in systems integration, software development, and IT security across both enterprise and consulting environments, he brings a practical understanding of secure system design and deployment. His credentials include PMP, CompTIA Security+, CEH, and AWS Certified Cloud Practitioner, reflecting his balanced expertise in governance, risk management, and cloud operations. Agus has worked with leading organizations such as Citi and Check Point Software Technologies, providing hands-on technical and security support across multi-cloud platforms.

Truman Ng is an experienced IT and AI systems consultant with more than 20 years of expertise in cloud computing, data analytics, and intelligent automation. He holds multiple professional certifications, including AWS Certified Solutions Architect, PMP®, and Huawei HCIE®. Truman has led digital transformation projects integrating AI and cloud technologies across manufacturing, logistics, and enterprise sectors. As an ACTA-certified trainer, he is recognized for his ability to simplify technical content and deliver structured, outcome-focused training experiences.
In this course, Truman provides learners with a practical understanding of AI principles and their implementation on AWS. His sessions emphasize hands-on learning using AWS AI services for model deployment, data analysis, and automation. Participants gain the ability to apply AI and machine learning concepts confidently, preparing them to achieve the AWS Certified AI Practitioner credential and contribute effectively to AI-driven projects in their organizations.

Review

Customer Reviews (18)

will recomemend Review by Course Participant/Trainee
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
. (Posted on 7/30/2025)
will recomemend Review by Course Participant/Trainee
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
. (Posted on 7/30/2025)
will recomemend Review by Course Participant/Trainee
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
. (Posted on 7/30/2025)
will recomemend Review by Course Participant/Trainee
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
. (Posted on 7/30/2025)
will recommend Review by Course Participant/Trainee
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
. (Posted on 4/17/2025)

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