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CASL - AI Agent with Hermes Agent

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.

Funding for this course is valid from 15 Aug 2026 to 14 Aug 2027. Register and complete the course within this period to qualify for funding support.

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.

CASL - AI Agent with Hermes Agent

Course Code: TGS-2026064176

CASL
PSEA
UTAP
SFEC
Absentee Payroll
MCES

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WSQ AI Agent with Hermes Agent equips participants with the knowledge and practical skills to build, deploy, and manage autonomous AI agents using the Hermes Agent framework. Participants will learn the fundamentals of Agentic AI, understand how AI agents reason, plan, use tools, and collaborate, and explore how intelligent agents can automate complex business and development workflows.

Through hands-on exercises, learners will build AI agents capable of interacting with Large Language Models (LLMs), external APIs, enterprise systems, and knowledge bases. They will learn to create single-agent and multi-agent workflows, integrate Retrieval-Augmented Generation (RAG) for context-aware responses, and implement memory, tool calling, and human-in-the-loop interactions to develop reliable and intelligent AI applications.

The course also covers best practices for agent orchestration, prompt engineering, evaluation, security, governance, and AI guardrails to ensure safe, scalable, and production-ready deployments. Participants will gain practical experience in designing AI agents that can automate customer support, software development tasks, business operations, research, and knowledge management.

By the end of the course, learners will be able to confidently design, develop, deploy, and manage AI agents with Hermes Agent, enabling organizations to improve productivity, streamline workflows, and build intelligent automation solutions for real-world applications.

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

Full Fee $750.00 Before GST

GST $67.50 9% of fee

Baseline Nett $442.50 SG/PR age 21+ · 50% funded

MCES / SME Nett $292.50 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

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 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: Fundamentals of Agentic AI and Hermes Agent

Topic 2: Building AI Agents with Hermes Agent

Topic 3: AI Agent Memory, Tools, and Knowledge Integration

Topic 4: Multi-Agent Collaboration and Workflow Automation

Topic 5: Deploying, Securing, and Optimizing AI Agents

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.
Minimum 18 years old

Minimum Software/Hardware Requirement

Software:

You will need the following for this course:

Hermes Agent desktop app – free
An API key for an AI model provider (the trainer will advise which one to use)

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).

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 PSEA (Singapore Citizens with a PSEA), or partly reimbursed by UTAP for NTUC members.

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.
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.

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 Agent Developer
AI Engineer
Machine Learning Engineer (agentic AI focus)
Data Scientist
AI Research Scientist (large language models)
Chatbot Developer
Automation Engineer
AI Solutions Architect
Conversational AI Designer
Workflow Automation Specialist
RAG and Knowledge Systems Engineer
Business Process Automation Analyst
Prompt Engineer
Software Developer (AI integration)
IT Operations Engineer.

Trainers

Mohan Pothula is a Certified Kubernetes Administrator (CKA) and enterprise architect with more than 20 years of experience designing secure, cloud-native platforms for financial, media and telecommunications organisations. He has held senior architecture roles at DBS Bank, SPH Media and Mediacorp, leading cloud migration, data platform modernisation and AI/ML enablement on AWS, Azure and Kubernetes. His DevOps expertise includes Docker, Jenkins, CI/CD pipelines, infrastructure as code and microservices, and he is experienced in operationalising AI models within cloud environments. He also holds certifications in AWS Solutions Architecture and Cloudera Administration, and he is known for architectures that satisfy stringent security and regulatory requirements. His work has included cloud migration, data governance, real-time analytics and API-driven architectures, which gives him a clear view of how AI workloads connect to enterprise data and systems. As a mentor and technical lead, he has guided engineering teams in adopting scalable cloud architectures and CI/CD pipelines that meet stringent regulatory and security standards.

In CASL - AI Agent with Hermes Agent, Mohan helps participants connect agentic AI concepts with the engineering needed to run agents in production. Learners study how AI agents reason, plan, use tools and collaborate, build agents with Hermes Agent that interact with large language models, external APIs, enterprise systems and knowledge bases, and create single-agent and multi-agent workflows with retrieval-augmented generation. Mohan focuses particularly on deploying, securing and optimising AI agents, applying his experience with containers, Kubernetes and cloud platforms to show how an agent can be packaged, deployed, monitored and scaled. He emphasises secure integration with enterprise systems, from protecting API keys and limiting permissions to keeping data handling compliant. He also discusses how to measure and optimise agent performance and cost, and how version control and automated deployment pipelines let teams improve agents without disrupting the workflows that depend on them. He also brings his CKA perspective to scaling multi-agent workflows, explaining how containerised agents can be scheduled, isolated and given appropriate resources on a Kubernetes cluster. Participants leave able to build, deploy and manage autonomous agents with Hermes Agent and to plan their operation with the discipline expected in enterprise environments.

Dr. Alfred Ang is an Agentic AI solution architect who designs and deploys multi-agent systems for real business use, including Hermes Agent workflows in his own operations. His hermes-video-pipeline project uses a Hermes Agent webhook to research, script, render, verify and publish YouTube videos for Tertiary Courses autonomously, and his hermes-demo repository sits alongside it in a GitHub portfolio of more than 300 public repositories. As Managing Director, CIO, CTO and Chief Instructional Designer of Tertiary Infotech Academy Pte Ltd, he leads agentic AI adoption and digital transformation, automating customer service, internal workflows, analytics and decision support with large language models, RAG pipelines and multi-agent systems. He works with n8n, Langflow, Flowise, OpenAI Agents SDK, Google Gemini Agent SDK, Claude Agent SDK, Microsoft AutoGen and CrewAI. On the infrastructure side he is a Certified Kubernetes Administrator (CKA) and Certified Kubernetes Application Developer (CKAD), runs his platforms in Docker containers through Coolify, and holds AWS Certified Solutions Architect and AI Practitioner credentials as well as the Microsoft Certified AI Engineer Associate (AI-102). He earned a PhD in Electrical Engineering from NUS and is an IBM certified instructor for the AI Practitioners course. His approach emphasises applied skills, ethical AI governance and sustainable digital adoption, and he holds a Certificate in AI Ethics and Governance (Senior Professional) from NTU. His public projects also include agents built with the Claude Agent SDK, n8n workflows with Telegram AI agents, and retrieval-augmented generation demos that answer questions from uploaded documents.

In CASL - AI Agent with Hermes Agent, Dr. Ang equips participants to build, deploy and manage autonomous agents with the Hermes Agent framework. Learners study how agents reason, plan, use tools and collaborate, then build agents that interact with large language models, external APIs, enterprise systems and knowledge bases. They create single-agent and multi-agent workflows, add retrieval-augmented generation for context-aware responses, and automate business and development processes. The final topic, deploying, securing and optimising AI agents, is where his CKA and CKAD experience comes to the fore: he shows how agents can be containerised and hosted, how secrets and API keys are protected, and how monitoring and logging reveal what an agent has done. His Certificate in AI Ethics and Governance from NTU informs his guidance on responsible deployment, from human oversight to data protection. As an ACTA-certified trainer, he keeps sessions practical, with learners building and testing their own agents throughout. He also shows how to evaluate an agent's output and cost, and how to optimise prompts, tools and model choices so that a workflow remains fast, accurate and affordable as it grows. Learners compare single-agent and multi-agent designs for the same task, learning when collaboration between agents adds value and when it simply adds complexity. He also discusses when a task should stay with a human, ensuring that autonomy is matched by appropriate accountability. Participants leave able to design and operate Hermes agents responsibly in their workplace. To see his agent pipelines, visit his GitHub portfolio at https://github.com/alfredang and connect with him on LinkedIn at https://www.linkedin.com/in/angchewhoe/

Tan Woei Ming is a data scientist and AI engineer with over 15 years of experience in machine learning, computer vision and intelligent automation. He has led projects involving predictive analytics, deep learning and AI-driven process optimisation within the semiconductor and manufacturing sectors. His expertise spans Python, PyTorch, TensorFlow and Hermes Agent, and he integrates natural language processing models with real-time applications to support intelligent decision-making and automation. He holds a Master's in Intelligent Systems from the National University of Singapore (NUS) and a First-Class Honours in Electrical and Electronic Engineering from NTU.

In CASL - AI Agent with Hermes Agent, Woei Ming teaches participants to design and deploy modular AI agent systems. Learners cover the fundamentals of agentic AI and Hermes Agent, build their own agents, add memory, tools and knowledge integration, set up multi-agent collaboration and workflow automation, and then deploy, secure and optimise their agents. His sessions emphasise practical implementation of agent pipelines and workflow orchestration. By blending theory with hands-on projects, he helps learners build adaptive AI agents that bring language models into real business applications, with the testing and safeguards needed to run them responsibly.

Dwight Nuwan Fonseka is an ACLP-certified trainer and Head of Data Science at Plano Pte. Ltd., with deep expertise in machine learning, data analytics and AI applications. His hands-on work includes developing predictive models and deep learning solutions in Python and R using TensorFlow and Keras, as well as RShiny dashboards. He brings a professional background in healthcare, finance and customer analytics, and an applied approach to AI that attends to both its opportunities and its risks. Dwight also holds a Masters in Education from NTU and has eight years of teaching experience in Singapore and overseas.

In CASL AI Agent with Hermes Agent, Dwight brings his applied AI and programming background to the Hermes Agent framework. He introduces the fundamentals of agentic AI and how agents reason, plan and use tools, then guides learners in building AI agents with Hermes Agent and integrating memory, tools and knowledge. Participants explore multi-agent collaboration and workflow automation before turning to deploying, securing and optimising their agents, where his focus on AI risk is especially relevant. Learners leave with hands-on experience of building and managing autonomous AI agents that automate business and development workflows in a controlled, responsible way.

Teh Siew Yee is a digital transformation and analytics leader with more than two decades of experience in data science, artificial intelligence and enterprise technology solutions. Having held senior roles at Standard Chartered, TikTok and Hewlett-Packard, Siew Yee brings deep expertise in AI governance, business intelligence and cloud-based analytics. Siew Yee holds a Master of IT in Business (Artificial Intelligence) from Singapore Management University and is an ACLP-certified trainer whose sessions combine case studies, role-plays and reflective exercises to make complex concepts practical.

In AI Agent with Hermes Agent, Siew Yee focuses on bridging AI theory with business problem-solving. Learners begin with the fundamentals of agentic AI and how agents reason, plan and use tools, then build their own AI agents with the Hermes Agent framework. They extend those agents with memory, tools and knowledge integration, explore multi-agent collaboration and workflow automation, and finish by deploying, securing and optimising agents for real use. Drawing on experience in AI governance and enterprise analytics, Siew Yee guides learners to build agents that handle complex reasoning reliably, helping their organisations unlock new productivity and innovation opportunities through agentic AI.