Course Details
Course Details
What You'll Learn
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
Assessment
- Written Exam
- Practical Exam
Course Info
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
Software:
You will need the following for this course:
- Python 3 – free
- Visual Studio Code – free
- A free Google Gemini API key – from Google AI Studio
Hardware: Windows PC or Mac laptop
Funding Eligibility Criteria
Self-sponsored learners (individuals)
- Singapore Citizens and Singapore Permanent Residents aged 21 and above.
- Up to 50% course fee funding. Singapore Citizens aged 40 and above receive up to 70% under the Mid-career Enhanced Subsidy (MCES).
- Singapore Citizens aged 25 and above can pay the remaining fee with SkillsFuture Credit.
Company-sponsored learners
- Singapore Citizens and Singapore Permanent Residents who are direct employees of the sponsoring company.
- Up to 50% course fee funding, or up to 70% for employees of SMEs (Enhanced Training Support for SMEs) and for Singapore Citizens aged 40 and above. An SME has no more than 200 employees or an annual turnover of no more than $100 million.
- Employers can also claim Absentee Payroll funding for employees who attend during working hours.
- Eligible companies can offset their out-of-pocket fees with SkillsFuture Enterprise Credit (SFEC).
Conditions for all funded learners
- Attendance is taken digitally with Singpass for every session, including the assessment.
- You must complete the course and pass all assessments (assessed as Competent).
- If these conditions are not met, the funding is clawed back and the learner or employer pays the full course fee.
- 9% GST is charged on the full course fee before funding.
- Promo and discount codes cannot be used on funded courses.
- Any balance after funding can be paid in cash, with SkillsFuture Credit, with PSEA (Singapore Citizens with a PSEA), or partly reimbursed by UTAP for NTUC members.
How to Apply SkillsFuture Credit Claim for Individuals
Singapore Citizens aged 25 and above can use their SkillsFuture Credit (base tier) to pay the course fee after funding. The $4,000 mid-career top-up cannot be used for this course.
- Register for this course as self-sponsored and tell us you will use SkillsFuture Credit. Do not pay the amount you plan to claim.
- We email you an invoice showing the course fee after funding.
- From 60 days before the course starts, and no later than the course start date, log in to MySkillsFuture with Singpass and click Claim credits.
- Click Submit a Claim and search for this course by its course code, TGS-2024042961.
- Select your class start date, enter the course fee payable after funding and the amount of credit to claim, then upload the invoice (PDF, JPG or PNG, under 4MB).
- Review, accept the terms and click Agree and Submit. The credit is paid directly to us; processing can take up to 14 working days.
Changing or withdrawing: cancel the claim on MySkillsFuture at least one day before the course starts. If your class date changes, cancel the claim and submit a new one with the new date.
How to Apply SkillsFuture Enterprise Credit (SFEC)
SFEC helps companies pay for employee training. The current SFEC ends on 30 November 2026, and a redesigned SFEC starts on 1 December 2026.
Current SFEC: classes ending on or before 30 November 2026
- Eligible companies received a one-off $10,000 credit, notified by letter to their Corppass administrator. Eligibility generally required at least 3 Singapore Citizen or PR employees and Skills Development Levy contributions.
- SFEC covers up to 90% of the company's out-of-pocket course fee after other subsidies.
- Check your company's SFEC eligibility and balance on EnterpriseSG.
- Register your Singapore Citizen or PR employee for a class that ends by 30 November 2026, as company-sponsored, and pay the course fee after funding.
- Your employee attends and completes the course. We submit the attendance and assessment results to SWDA.
- No separate claim is needed. SFEC is calculated automatically once the course fee grant is approved and is paid quarterly to your company's IRAS GIRO or PayNow Corporate account.
Any unused balance of the current SFEC expires on 30 November 2026.
Redesigned SFEC from 1 December 2026
Companies with at least 3 resident employees receive a fresh $10,000 in an online SFEC wallet that offsets out-of-pocket fees upfront at enrolment, instead of reimbursing them afterwards. SWDA has not yet published the support rates and claim steps; see OurWorkforce or our SFEC guide.
How to Apply UTAP (NTUC Members)
NTUC members can claim 50% of the unfunded course fee under the Union Training Assistance Programme (UTAP), capped at $250 a year (aged below 40) or $500 a year (aged 40 and above). The cap is shared with UTAP claims for AI tool subscriptions.
Eligibility: you must be an NTUC member paying full membership fees, with your membership paid up before and during the course and when you claim. The course must not be fully paid for by your employer or another source.
- Make sure your NTUC membership is paid up before the course starts.
- Register for this course with us and pay the course fee after funding and SkillsFuture Credit.
- Attend at least 75% of the course and sit all assessments.
- Within 6 months after the course ends, go to the NTUC U Portal, open UTAP under E-services, log in with Singpass and choose Course Fee Claim.
- Enter the nett course fee you paid (after all subsidies and SkillsFuture Credit, including GST), and upload your invoice or receipt and your certificate or result slip (PDF, JPG or PNG, up to 5MB each).
- NTUC usually pays the claim within 4 weeks of submission.
Read more in our UTAP guide.
How to Apply PSEA
Singapore Citizens with a Post-Secondary Education Account (PSEA), which stays open until around the year you turn 31, can use it to pay the course fee after funding for PSEA-approved courses. You can also use a sibling's PSEA after your own has been used up.
- Check that this course shows the PSEA tag on its MySkillsFuture page.
- Check your PSEA balance on MOE's Student Finance System with Singpass.
- Download and complete the PSEA withdrawal form, then submit it to us.
- We submit the withdrawal request to MOE. You (and your sibling, if you are using their account) authorise it in the Student Finance System. Nothing is withdrawn without this authorisation.
- MOE pays us directly. If you have already paid, we refund the amount covered by PSEA.
More details: MOE PSEA overview.
Appeal Process
If you disagree with an assessment decision, you have the right to appeal.
- When the assessor gives you feedback, say whether you agree with the outcome. If you agree, you and the assessor sign the Assessment Summary Record; if you disagree, do not sign it.
- Discuss the decision with the assessor or the assessment manager first.
- If you are still not satisfied, tell the assessor you intend to appeal. The assessor records this in the feedback section of the Assessment Summary Record and informs the assessment manager.
- Lodge your appeal within 7 days, giving your reasons, using the Candidate Appeal Form. The assessor can help you write and lodge it.
- An Assessment Appeal Panel reviews the information from you and the assessor and makes a decision. A record of the appeal and its outcome is kept.
- You will be told the outcome within 2 weeks of lodging the appeal. The panel's decision is final.
Job Roles
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
Trainers
Google Gemini features throughout Dr. Alfred Ang's agent work, and the Google Gemini Agent SDK is one of the frameworks he uses to design multi-agent systems, alongside the OpenAI Agents SDK, the Claude Agent SDK, Microsoft AutoGen, CrewAI, n8n, Langflow and Flowise. A full-stack AI developer and Agentic AI solution architect, he builds production-ready AI applications from frontend to backend, including LLM orchestration, RAG pipelines and cloud deployment on AWS and Kubernetes. He serves as Managing Director, CIO, CTO and Chief Instructional Designer of Tertiary Infotech Academy Pte Ltd and is the founder of Tertiary Courses. His GitHub portfolio of more than 300 public repositories includes several Gemini-powered builds: n8n-ragdemo is a no-code RAG demo in which a Telegram AI agent running on Google Gemini answers questions from uploaded PDFs; bakerycourses-demo is a lead-magnet site with an n8n and Gemini course chatbot that deliberately uses context-stuffing instead of RAG; and digitalhuman builds voice-enabled avatars trained on a client's content through RAG, with Gemini as one of its model options. He is equally at home with Streamlit, which powers his ssg-ato-generator and wsq-courseware-generator-claude-streamlit apps. His credentials include a PhD in Electrical Engineering from NUS, an MSc in Electrical and Electronic Engineering from NTU, Microsoft Certified AI Engineer Associate (AI-102) and Data Scientist (DP-100), and AWS Certified Solutions Architect and AI Practitioner. His logomaker project also uses Gemini image models to turn text descriptions into downloadable logo options in the browser.
In WSQ Develop Multi AI Agent Applications with Gemini Agent ADK, Dr. Ang takes learners from concepts to a deployed application. The first topic gives an overview of agentic AI in the Gemini ADK, covering how agents reason, call tools and coordinate, and how the ADK structures them. The second topic builds a multi-agent app, splitting a task between specialised agents and defining how they pass work to one another. Topic three adds agentic RAG, where his experience with both retrieval and context-stuffing approaches helps learners decide when a vector store is genuinely needed and how to keep answers grounded in source documents. The final topic brings everything together in an agentic AI app with a Streamlit front end, so learners finish with an interface they can demonstrate to colleagues. He emphasises the practical details that separate a demo from a dependable application: clear agent instructions, sensible tool boundaries, testing with realistic questions and checking what each agent actually returned. His NTU Certificate in AI Ethics and Governance (Senior Professional) informs the discussion of responsible deployment and human oversight. As an ACTA-certified trainer and DACE-certified curriculum developer, he runs the course as a sequence of guided builds, each extending the last, with plenty of time to experiment and debug. Learners leave with a working multi-agent Gemini application and the confidence to adapt it to their own use cases. To see his Gemini and Streamlit projects, explore his GitHub portfolio at https://github.com/alfredang and connect with him on LinkedIn at https://www.linkedin.com/in/angchewhoe/
Yeo Hwee Theng is a data science leader and AI strategist with extensive experience driving enterprise AI adoption across healthcare, finance and government. As Data & Analytics Product Lead at Amplify Health, she oversees large-scale AI-driven transformation initiatives and data platform architecture, and leads machine learning projects focused on data-driven decision-making. She previously served as AI & Data Architect at Huawei International and Senior Data Scientist at DataRobot, implementing advanced AI and analytics solutions across the Asia-Pacific region. 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 Multi AI Agent Applications with Gemini Agent ADK, she focuses on practical strategies for bringing large language models into real workflows. Learners begin with an overview of agentic AI in Google's Gemini Agent Development Kit, then build a multi-agent application in which specialised agents share the work. They go on to create an agentic Retrieval-Augmented Generation (RAG) solution that grounds answers in their own content, and finish by building an agentic AI app with Gemini ADK and a Streamlit front end. Her enterprise perspective keeps productivity, reliability and business value in view as they build, so participants leave with working Gemini-based agents and a clear path to scale them.
Tan Woei Ming is a data scientist and AI engineer with over 15 years of experience in machine learning, deep learning and computer vision across industrial and enterprise environments. His expertise spans predictive analytics, neural network optimisation and real-time data processing for automation systems, and he has led projects in yield optimisation, robotic control and AI model deployment, working with frameworks such as TensorFlow and PyTorch. 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.
In WSQ - Develop Multi AI Agent Applications with Gemini Agent ADK, Woei Ming applies his model deployment experience to agentic AI built on Google's Agent Development Kit. Learners begin with an overview of agentic AI in Gemini ADK, build a multi-agent application, create an agentic retrieval-augmented generation (RAG) solution, and then develop a complete agentic AI app with Gemini ADK and Streamlit. His sessions focus on prompt design, model integration and connecting agents into end-to-end workflows. With his strong foundation in deep learning, he helps participants understand how the pieces fit together, so they can build, test and deploy multi-agent applications for real business and engineering challenges.
Teh Siew Yee is a data analytics and digital transformation leader with more than two decades of experience in the technology, banking and manufacturing sectors. Siew Yee has held key leadership roles at Standard Chartered, Hewlett-Packard, TikTok and SIA Engineering, leading 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, and is an ACLP-certified trainer recognised for an engaging, industry-relevant teaching style.
In Develop Multi AI Agent Applications with Gemini Agent ADK, Siew Yee applies this AI strategy experience to building agentic applications on Google's Gemini models. Learners start with an overview of agentic AI in the Gemini Agent Development Kit, then build a multi-agent app in which agents share work and use tools. They create an agentic RAG application that grounds responses in documents and complete the course by building an agentic AI app with a Streamlit front end. Siew Yee's sessions emphasise responsible AI use and business process innovation, so that through structured, hands-on practice learners can apply Gemini-based agents to real organisational problems.
Truman Ng is an AI infrastructure engineer and technology consultant whose expertise lies in connecting large-scale AI models with enterprise infrastructure, so that organisations can implement AI solutions that are secure, scalable and efficient. With more than 20 years of experience in cloud computing, network architecture and intelligent automation, he has delivered training programmes worldwide in DevOps, cybersecurity and AI system integration, and has taught the technical implementation of Google Gemini models in hybrid and enterprise environments. He holds PMP and Huawei HCIE certifications and is an ACTA-certified trainer.
In WSQ Develop Multi AI Agent Applications with Gemini Agent ADK, Truman takes learners from an overview of agentic AI in Google's Agent Development Kit to building their own multi-agent applications. Participants create a multi-agent app with Gemini ADK, build an agentic RAG solution that grounds agents in their own data, and develop a complete agentic AI application with Gemini ADK and Streamlit. His sessions cover system integration, API orchestration and cloud deployment of LLM-powered solutions, with practical demonstrations throughout. Learners finish able to build reliable, high-performance agent applications that fit within their organisation's IT and security frameworks.
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