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WSQ - Develop Multi AI Agent Applications with Gemini Agent ADK

WSQ - Develop Multi AI Agent Applications with Gemini Agent ADK

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Master the development of advanced Artificial Intelligence (AI) solutions by leveraging the power of Google Gemini's Large Language Models (LLMs). This course begins with a comprehensive overview of LLMs, their industrial use cases, and introduces you to Google Gemini. Explore multimodal prompting through Google AI Studio and Vertex AI, gaining practical experience with workflows that integrate Gemini's capabilities.

Dive deeper into building LLM-driven applications using Langchain and Gemini, automating workflows and creating intelligent AI agents. Additionally, learn how to implement Retrieval Augmented Generation (RAG) technology by managing document embedding, splitting, and utilizing vector databases. This course equips you with the skills to design, develop, and evaluate LLM applications for real-world deployment.

Learning Outcomes

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

LO1: Analyze the range of LLM applications using Generative AI (GAI) and identify their industrial use cases.
LO2: Establish Google Gemini GAI designs and assess improvements on engineering processes.
LO3: Develop LLM applications and assess its feasibility.
LO4: Evaluate the performance effectiveness of Retrieval Augmented Generation (RAG).

Course Brochure

Download WSQ - Develop Artificial Intelligence and Large Language Model (LLM) Applications with Google Gemini Brochure

Skills Framework

This course follows the guideline of Artificial Intelligence Application AER-TEM-4026-1.1 under Aerospace 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.

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-2024042961)

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-2024042961

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 Overview of Agentic AI in Gemini ADK
Topic 2 Build A Multi Agent App with Gemini ADK
Topic 3 Build Agentic AI RAG in Gemini ADK
Topic 4 Build a Agenti AI App with Gemini Agent ADK and Streamlit

Final Assessment

Written Assessment - Short Answer Questions (WA-SAQ)
Practical Performance (PP)

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 Age Group: 21 to 65 years old

Minimum Software/Hardware Requirement

You can download and install the following software:

Google Gemini

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 of age 21 and above
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

Robotics Engineer
ROS Developer
Automation Engineer
Robotics System Integrator
Robotics Researcher
Autonomous Vehicle Engineer
Drone Systems Developer
Robotic Manipulation Specialist
AI & Robotics Developer
Embedded Systems Engineer (with robotics focus)
Machine Vision Engineer
Mechatronics Engineer
Industrial Robot Programmer
Robot Simulation Specialist
IoT Engineer (with robotics applications).

Trainers

Tan Woei Ming: Tan Woei Ming is a data scientist and AI engineer with more than 15 years of experience in machine learning, deep learning, and computer vision applications across industrial and enterprise environments. He holds a Master’s in Intelligent Systems from the National University of Singapore and a First-Class Honours in Electrical and Electronic Engineering from Nanyang Technological University. His expertise spans predictive analytics, neural network optimization, and real-time data processing for automation systems, having led projects in yield optimization, robotic control, and AI model deployment.

In “Develop Artificial Intelligence and Large Language Model (LLM) Applications with Google Gemini,” Woei Ming guides learners through the design and implementation of Gemini-powered AI systems. His sessions focus on prompt optimization, model integration, and multimodal application development using Google’s AI tools. With a strong foundation in deep learning frameworks such as TensorFlow and PyTorch, he helps participants build end-to-end AI workflows that combine data analytics, reasoning, and generative intelligence for real-world business and engineering challenges.

Yeo Hwee Theng: Yeo Hwee Theng is a data science leader and AI strategist with extensive experience driving enterprise AI adoption across healthcare, finance, and government sectors. As the Data & Analytics Product Lead at Amplify Health, she oversees large-scale AI-driven transformation initiatives and data platform architecture. Previously, she served as an AI & Data Architect at Huawei International and Senior Data Scientist at DataRobot. She holds a Master of Technology in Enterprise Business Analytics from the National University of Singapore and an Advanced Certificate in Learning and Performance (ACLP).

In “Develop Artificial Intelligence and Large Language Model (LLM) Applications with Google Gemini,” Hwee Theng demonstrates how to harness Gemini’s multimodal capabilities to power contextual understanding and decision intelligence. Her training emphasizes practical strategies for integrating LLMs into analytics workflows, enabling organizations to enhance productivity, automate insights, and scale intelligent applications. Through hands-on projects, she equips participants to design, fine-tune, and deploy Gemini-based AI systems that deliver measurable business value.

Teh Siew Yee: Teh Siew Yee is an experienced data analytics and digital transformation leader with over two decades of experience in the technology, banking, and manufacturing sectors. She has held key leadership roles in organizations such as Standard Chartered, Hewlett-Packard, TikTok, and SIA Engineering, where she led data governance and AI strategy initiatives. Siew Yee holds a Master of IT in Business (Artificial Intelligence) from Singapore Management University and a Bachelor of Engineering (Electrical and Electronic) from Nanyang Technological University. She is also an ACLP-certified trainer recognized for her engaging, industry-relevant teaching style.

In “Develop Artificial Intelligence and Large Language Model (LLM) Applications with Google Gemini,” Siew Yee focuses on enabling participants to integrate Gemini AI into data analytics pipelines and digital transformation frameworks. Her sessions emphasize responsible AI use, ethical model deployment, and optimization of AI for business process innovation. Through structured learning and applied projects, she helps learners master Gemini’s tools for knowledge reasoning, automation, and generative data insights.

Truman Ng: Truman Ng is a senior technology consultant and AI infrastructure engineer with more than 20 years of experience in cloud computing, network architecture, and intelligent automation. He is a PMP, ACTA, and Huawei HCIE-certified professional who has delivered global training programs in DevOps, cybersecurity, and AI system integration. His expertise lies in connecting large-scale AI models with enterprise infrastructure, enabling organizations to implement secure, scalable, and efficient AI solutions.

In “Develop Artificial Intelligence and Large Language Model (LLM) Applications with Google Gemini,” Truman focuses on the technical implementation of Gemini AI models in hybrid and enterprise environments. His sessions cover system integration, API orchestration, and cloud deployment of LLM-powered solutions. Through practical demonstrations, he teaches participants how to build reliable, compliant, and high-performance AI ecosystems that align with organizational IT and security frameworks.

James Lee Kin Nam: James Lee Kin Nam is an accomplished digital media and IT educator with more than 20 years of experience in creative technology, automation, and applied computing. An Adobe Certified Expert and ACLP-qualified instructor, he has trained corporate and academic professionals in digital transformation, AI-enhanced creativity, and productivity tools. His instructional design philosophy focuses on simplifying complex technical concepts into accessible, experiential learning modules.

In “Develop Artificial Intelligence and Large Language Model (LLM) Applications with Google Gemini,” James teaches participants to design intuitive, human-centric AI applications that merge creativity with automation. His sessions highlight Gemini’s capabilities in natural language processing, image generation, and interactive chatbot development. By blending technical depth with creative insight, he empowers learners to build Gemini-driven applications that enhance user engagement, streamline workflows, and expand the boundaries of AI innovation.