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WSQ - Agentic AI Applications with Codex

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.

TSC Title: Artificial Intelligence Application
TSC Code: AER-TEM-4026-1.1

Funding for this course is valid from 27 Dec 2023 to 26 Dec 2027. Register and complete the course within this period to qualify for funding support.

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

LO1: Analyze range of agentic AI applications and identify their strengths, limitations, and industry applicability.
LO2: Establish the correlation between agentic AI algorithm design and efficiency, and evaluate process improvement.
LO3: Assess agentic AI application effectiveness evaluation methods.
LO4: Evaluate agentic AI applications focusing on performance effectiveness and comparative analysis.

Download Course Brochure

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 - Agentic AI Applications with Codex

Course Code: TGS-2023041081

WSQ
SFC
PSEA
SFEC
Absentee Payroll
MCES

13 Review(s) | Add Your Review

This course equips learners with practical skills to design, build, test, and optimise agentic AI applications using Codex. Participants will use Codex as an AI coding agent to translate application requirements into working software, understand existing codebases, generate and refactor code, diagnose issues, and validate solutions through testing and review.

Learners will explore the core components of agentic applications, including structured workflows, tool use, memory, context management, retrieval-augmented generation (RAG), action loops, human approvals, and multi-agent coordination. They will connect applications to external systems and data sources using Model Context Protocol (MCP) tools and develop reusable Skills for consistent, task-specific workflows.

The course covers the end-to-end development process, from defining use cases and planning system architecture to implementing interfaces, integrating APIs, managing data, and deploying functional applications. Participants will also use Codex to create tests, evaluate outputs, troubleshoot failures, improve reliability, and document their solutions.

Emphasis is placed on secure coding, permission control, data privacy, responsible AI practices, and human oversight. By the end of the course, learners will be able to use Codex to develop production-oriented agentic AI applications that can retrieve information, use tools, complete multi-step tasks, and support real-world business processes.

This course is part of our AI training in Singapore, where you can browse all our AI courses. See more ChatGPT and Codex training.

Full Fee $800.00 Before GST

GST $72.00 9% of fee

Baseline Nett $472.00 SG/PR age 21+ · 50% funded

MCES / SME Nett $312.00 SG age 40+ · 70% funded

SkillsFuture Enterprise Credit (SFEC)

Eligible companies can use their $10,000 SFEC to cover up to 90% of out-of-pocket course fees for classes ending on or before 30 Nov 2026. A redesigned SFEC starts on 1 Dec 2026.

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

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 Form Submit PSEA Form

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

Topic 1: Agentic AI Application Planning and Development with Codex

Topic 2: Building Reusable AI Workflows with Codex Skills and MCP Tools

Topic 3: Developing RAG and Multi-Agent Applications with Codex

Topic 4: Testing, Evaluating and Optimising Agentic AI Applications

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 Year Group : 21-65 years old

Minimum Software/Hardware Requirement

Software:

You will need the following for this course:

A ChatGPT Plus (or higher) subscription – required
ChatGPT desktop app – free download
Visual Studio Code – free
Git – free

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).

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-2023041081.
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 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

AI Developer
Machine Learning Engineer
AI Solutions Architect
Data Scientist
AI Agent Engineer
Software Developer
AI Product Manager
Data Engineer
Prompt Engineer
AI Automation Consultant
Application Developer
R&D Engineer (AI)
Technical Consultant (AI)
Business Intelligence Analyst
Innovation Manager
Systems Analyst
Tech Project Manager
Automation Engineer
AI Research Assistant
Solution Developer

Trainers

Dr. Alfred Ang works with AI coding agents as everyday engineering tools, which is exactly the perspective this course needs. A full-stack AI developer and Agentic AI solution architect, he designs and deploys AI-powered applications end to end, from frontend and backend systems to LLM orchestration, RAG pipelines, multi-agent systems and cloud-native infrastructure on AWS and Kubernetes. His agent toolkit spans the OpenAI Agents SDK, Claude Agent SDK, Google Gemini Agent SDK, Microsoft AutoGen, CrewAI, n8n, Langflow and Flowise. He is Managing Director, CIO, CTO and Chief Instructional Designer of Tertiary Infotech Academy Pte Ltd, holds a PhD in Electrical Engineering from NUS, and is a Microsoft Certified AI Engineer Associate (AI-102) and Data Scientist (DP-100) and an AWS Certified Solutions Architect and AI Practitioner. His GitHub portfolio of more than 300 public repositories includes codex-demo, a dependency-free cooking and baking course catalogue with an AI-assisted course adviser; skills, a published collection of reusable Claude Code skills for tasks such as README generation, Docker Hub pushes and secret scanning; wsq-courseware-generator-claude-streamlit, which automates courseware creation with the Claude Agent SDK; and n8n-ragdemo2, which ingests course brochures into Supabase, Pinecone or Qdrant vector databases for a RAG chatbot. Together they show the reusable workflows, retrieval and agent coordination at the heart of agentic applications. He is also an ACTA-certified trainer and DACE-certified curriculum developer, and holds an MSc in Electrical and Electronic Engineering from NTU and a B.Sc (Hons) in Physics from NUS.

In WSQ - Agentic AI Applications with Codex, Dr. Ang shows learners how to use Codex as an AI coding agent that turns requirements into working, tested software. The first topic covers planning and developing agentic AI applications with Codex: translating requirements, understanding an existing codebase, generating and refactoring code and diagnosing issues. Learners then build reusable AI workflows with Codex skills and MCP tools, before developing RAG and multi-agent applications that combine tool use, memory, context management, action loops, human approvals and multi-agent coordination. The final topic focuses on testing, evaluating and optimising these applications. Because he maintains reusable skills and RAG pipelines of his own, he can show learners how to structure instructions so an agent behaves consistently, how to give it just enough context and when to insist on human approval before an action runs. He is equally firm on verification: every change an agent makes should be read, tested and reviewed, and secrets must never be pasted into prompts or code. Sessions are hands-on, with learners directing Codex through a realistic build. As a WSQ course it also prepares learners for assessment, and they leave able to plan, build and evaluate an agentic application with confidence. He also discusses how to keep agent costs predictable and how to log an agent's actions so that its decisions can be reviewed later. To explore his agent and RAG projects, learners can view his GitHub portfolio at https://github.com/alfredang and connect with him on LinkedIn at https://www.linkedin.com/in/angchewhoe/

Solomon Soh is a data scientist and AI trainer and a Certified AI Engineer specialising in deep learning, reinforcement learning and natural language processing. With hands-on expertise in AI model development and deployment, he has carried out projects integrating generative AI techniques into real-world business applications, and his current focus areas are generative AI, large language models and AI-driven application design. As a Data Science Trainer with IBM Singapore he has coached teams on NLP, computer vision and chatbot projects, earning a 96% learner satisfaction rating, and his career also includes Workforce Optimizer, Certis Cisco, Ernst & Young and IQVIA.

In WSQ Agentic AI Applications with Codex, Solomon applies his generative AI and application design experience to building software with an AI coding agent. Learners plan and develop agentic AI applications with Codex, build reusable AI workflows with Codex skills and MCP tools, develop retrieval-augmented generation (RAG) and multi-agent applications, and then test, evaluate and optimise what they have built. His training emphasises hands-on coding, applied labs and project-based learning, with attention to domains such as automation, customer engagement and analytics. Participants leave confident in using Codex to translate requirements into working agentic AI applications and to assess their quality before deployment.

Sanjiv Venkatram is a consultant and ACTA-certified trainer with rich expertise in business intelligence, data analytics and business applications, including CRM systems. As CEO of Prudentia Consulting, he promotes the active use of the Microsoft platform, and his career includes roles at Microsoft across the US and APAC, Cognizant, Yazaki North America and Oracle. He has delivered large-scale BI and analytics projects in financial planning, manufacturing and education, among them an APAC-wide Power BI dashboard backed by a SQL-based KPI lake and a budget audit tool that captured inputs from countries around the world.

In this course, Sanjiv applies his data analytics and business applications experience to guide learners in using AI coding agents for real-world use cases. Participants plan and develop agentic AI applications with Codex, build reusable AI workflows with Codex skills and MCP tools, and create retrieval-augmented generation (RAG) and multi-agent applications. The final topic covers testing, evaluating and optimising these applications so they hold up in practice. Sanjiv emphasises integrating AI into enterprise workflows, helping participants design solutions that improve productivity and decision-making, and his sessions combine conceptual clarity with interactive labs so learners gain practical experience alongside the theory.

Alfred Yap is an experienced trainer and ICT consultant with decades of expertise in cybersecurity, cloud computing and enterprise technologies, and his mission as a trainer is to bridge emerging technologies such as generative AI with the needs of organisations. An ACLP-certified trainer, he has conducted ICT-related training across multiple domains, helping organisations adopt new digital tools. His teaching draws on a solid foundation in instructional design and applied learning, and he is known for making technical concepts accessible to diverse groups of learners, including in beginner-level network security training on password policies, secure browsing and basic risk management.

For WSQ - Agentic AI Applications with Codex, Alfred draws on his strong background in cloud systems and secure digital infrastructure. Learners use Codex as an AI coding agent to plan and develop agentic applications, build reusable AI workflows with Codex skills and MCP tools, and develop RAG and multi-agent applications. The course then turns to testing, evaluating and optimising those applications. Throughout, Alfred emphasises permission control, governance and security best practices, so that agents act within safe limits. His structured, hands-on teaching style prepares participants to apply AI coding agents confidently in production-ready business applications.

Review

Customer Reviews (13)

Average Rating: 5.0/5 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

A lot to go through in 2 days, hope I can remember enough from the notes to keep on practicing. (Posted on 11/8/2026)

Average Rating: 3.7/5 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

N/A (Posted on 11/8/2026)

Average Rating: 5.0/5 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

N/A (Posted on 9/25/2026)

Average Rating: 3.7/5 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

the requirement that a paid codex is required isn't prominent enough and many attendees (including me) were caught by surprise. some purchased a Plus or Pro plan just for this training and once tokens ran out, some paid extra.

second problem with this is the time ... codex tokens for normal plus or even enterprise-standard plans can run out quite quickly. then its either you have to wait out the 5 hours or you have to pay extra, which isn't practical for a course that spans 2 days.

third is the virtual class. the connection on the first day was very bad with screen-freezing, and on the second day, the trainer accidentally disconnected the Google Meet and didn't respond to the WhatsApp group to reconnect. more half the afternoon's session (which hopefully is used only for the assessment) is lost. (Posted on 9/25/2026)

Average Rating: 5.0/5 Review by Course Participant/Trainee