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WSQ - AWS Certified AI Practitioner Training

WSQ - AWS Certified AI Practitioner Training

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.

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 WSQ - AWS Certified AI Practitioner Training Brochure

Skills Framework

This course follows the guideline of Artificial Intelligence Application in Product Development ICT-TEM-3034-1.1 under ICT Skills Framework

Certification

Certificate of Completion from Tertiary Infotech - Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Completion from Tertiary Infotech.
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.
External Certification - The participant will be able to attempt the AWS Certified AI Practitioner exam after attending this course. Upon passing the exam, you will receive the AWS Certified AI Practitioner accreditation. This certification validates that the individual possesses the skills and knowledge necessary to design and deploy scalable, highly available, and fault-tolerant systems on the Amazon Web Services (AWS) platform. It demonstrates proficiency in various aspects of AWS architecture, including designing and deploying applications on AWS, selecting appropriate AWS services based on requirements, designing highly available and scalable systems, and implementing cost-effective solutions.

AWS Skill Builder

We are authorised AWS reseller of AWS Skill Builder. If you would like to subscribe to AWS Skill Builder, please register you interest here.

Certification Exam at Pearson Vue

Once you are prepared for the exam, you can register for the AWS Certified AI Practitioner Exam here. We are Authorised Pearson Vue Testing Center. You can take the certification exam at our test center. Note that the course fee does not include the certification exam fee.

You can purchase the exam voucher (one of the lowest prices in Singapore) at AWS Foundational Certification Exam Voucher

WSQ Funding

WSQ funding is only applicable to Singaporeans and PR. Subject to eligibility, the funding support is subjected to funding caps.

Effective for courses starting from 1 Jan 2024
Full Fee	GST	Nett Fee after Funding (Incl. GST)
		Baseline	MCES / SME
$900.00	$81.00	$531.00	$351.00

Baseline: Singaporean/PR age 21 and above
MCES(Mid-Career Enhanced Subsidy): S'porean age 40 & above

Upon registration, we will advise further on how to tap on the WSQ Training Subsidy.

You can pay the nett fee (after the WSQ training subsidy) by the following :

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-2023039183)

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.

Course Code: TGS-2024049338

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.

Course Cancellation/Reschedule Policy

You can register your interest without upfront payment. There is no penalty for withdrawal of the course before the class commerce.
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

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.

Final Assessment

Written Assessment (SAQ)
Practical Performance

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 SkillsFuture Singapore's (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 SkillsFuture Singapore's (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), SSG 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

Note

SSG 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

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

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

Quah Chee Yong: Quah Chee Yong is an AI and data analytics specialist with more than 15 years of experience in software engineering, cloud computing, and applied machine learning. He has delivered numerous AI and analytics programs under national initiatives such as IMDA’s TechSkills Accelerator and SGUnited, helping professionals bridge technical skills with business intelligence. As an ACLP-certified trainer, Chee Yong is known for his ability to simplify complex AI concepts and translate them into practical, real-world applications. His expertise spans Python, TensorFlow, and AWS SageMaker, with a focus on building AI solutions for enterprise data systems.

In this course, Chee Yong helps learners develop a strong foundation in AI principles, cloud integration, and practical implementation using AWS tools. His sessions focus on the fundamentals of machine learning, responsible AI, and generative AI services within the AWS ecosystem. Learners gain hands-on experience in applying AI concepts to real-world business challenges, equipping them to earn the AWS Certified AI Practitioner credential with confidence.

Amin Mahetar: Amin Mahetar is a cloud and AI architect with over two decades of experience in cloud infrastructure, cybersecurity, and AI-driven transformation. He has held leadership and consulting roles at global organizations such as Cisco, GovTech, and Deutsche Bank, implementing large-scale automation and machine learning solutions. Amin is an AWS Certified Solutions Architect, Google Cloud Professional Architect, and CISSP, combining technical excellence with strategic insight. His expertise lies in applying AI and automation to modernize cloud-based systems securely and efficiently.

In this course, Amin introduces learners to the practical use of AWS AI services such as SageMaker, Bedrock, and Comprehend for intelligent automation and data-driven decision-making. His sessions emphasize the responsible deployment of AI technologies and their alignment with organizational goals. Learners gain a holistic understanding of AWS AI tools, preparing them to design, evaluate, and manage AI solutions that enhance innovation and operational excellence.

Mohan Pothula: 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: Agus Salim is a seasoned IT and systems engineer with more than 20 years of experience in network infrastructure, cybersecurity, and cloud operations. He has worked with enterprise clients across the Asia-Pacific region to implement digital transformation projects integrating AI, automation, and cloud computing. As a certified ACLP trainer and AWS practitioner, Agus brings deep technical knowledge and a strong focus on applied learning, helping learners bridge foundational AI concepts with real-world business use cases.

In this course, Agus introduces participants to the key AWS AI and ML services that support intelligent data processing and predictive analytics. His sessions focus on the fundamentals of AI workflows, natural language processing, and computer vision applications using AWS. Learners gain practical experience in building and deploying AI-enabled solutions that enhance decision-making, efficiency, and innovation within modern organizations.

Truman Ng: 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.

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WSQ - AWS Certified AI Practitioner Training

Learning Outcomes

Course Brochure

Skills Framework

Certification

AWS Skill Builder

Certification Exam at Pearson Vue

WSQ Funding

SkillsFuture Enterprise Credit (SFEC)

SkillsFuture Credit (SFC)

UTAP

PSEA

Fee

Course Information

Post-Course Support

Course Cancellation/Reschedule Policy

Course Details

Course Info

Promotion Code

Minimum Entry Requirement

Minimum Software/Hardware Requirement

About Progressive Wage Model (PWM)

Funding Eligility Criteria

Steps to Apply Skills Future Claim

SkillsFuture Level-Up Program

Get Additional Course Fee Support Up to $500 under UTAP

Steps to Apply UTAP

Note

Appeal Process

Job Roles

Trainers

Customer Reviews (18)

Write Your Own Review

You're reviewing: WSQ - AWS Certified AI Practitioner Training

How do you rate this product? *

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About Us

Training Grants and Subsidies

Authorised Training Partners

Authorized Testing Centers

Approved Training Organizations

Approved Suppliers

Regional Training Centers

Contact Us Information

Information

Enquires

Training Grant and Subsidy

Our Websites

Certified Trainers

WSQ - Develop Generative AI Apps in Azure AI Foundry (AI-3016)