Course Details
Course Details
What You'll Learn
Topic 1 SDLC Automation
Implement CI/CD pipelines
Integrate automated testing into CI/CD pipelines
Build and manage artifacts
Implement deployment strategies for instance, container, and serverless environments
Topic 2 Configuration Management and IaC
Define cloud infrastructure and reusable components to provision and manage systems throughout their lifecycle
Deploy automation to create, onboard, and secure AWS accounts in a multi-account or multi-Region environment
Design and build automated solutions for complex tasks and large-scale environments
Topic 3 Resilient Cloud Solutions
Implement highly available solutions to meet resilience and business requirements
Implement solutions that are scalable to meet business requirements
Implement automated recovery processes to meet RTO and RPO requirements
Topic 4: Monitoring and Logging
Configure the collection, aggregation, and storage of logs and metrics
Audit, monitor, and analyze logs and metrics to detect issues
Automate monitoring and event management of complex environments
Topic 5: Incident and Event Response
Manage event sources to process, notify, and take action in response to events
Implement configuration changes in response to events
Troubleshoot system and application failures
Topic 6: Security and Compliance
Implement techniques for identity and access management at scale
Apply automation for security controls and data protection
Implement security monitoring and auditing solutions
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 Year Group : 21-65 years old
Minimum Software/Hardware Requirement
Software:
You will need the following for this course:
- An AWS account – Free Tier available; a credit card is required to sign up
- Docker Desktop – free for personal use
- 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), 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-2025054815.
- 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
- DevOps Engineer
- AWS Solutions Architect
- Cloud Engineer
- Systems Administrator
- Software Developer
- IT Project Manager
- Infrastructure Engineer
- Network Administrator
- Security Engineer
- Application Developer
- IT Operations Manager
- Site Reliability Engineer
- Full Stack Developer
- Data Engineer
- Technical Architect
Trainers
Trainers
Nicholas Lu is an experienced MLOps and DevOps engineer with deep expertise in Kubernetes, Terraform, and distributed data platforms. Over the past decade, he has worked in roles spanning Site Reliability Engineering, MLOps, and data engineering at Motional, Arvato Bertelsmann, and True Digital. A Certified Kubernetes Administrator (CKA) and AWS Solutions Architect Professional, Nicholas has built large-scale, cloud-agnostic infrastructures leveraging Helm, ArgoCD, Kubeflow, and GitOps principles. His work bridges the gap between data science and platform reliability, enabling efficient, automated machine learning operations across EKS and GKE environments.
In the Certified Kubernetes Administrator Training, Nicholas brings his practical experience in managing production-grade clusters and integrating DevOps pipelines for AI/ML workflows. His instruction focuses on real-world scalability, performance monitoring, and IaC automation—key components for mastering Kubernetes administration. Learners benefit from his ability to connect complex cloud-native technologies with hands-on problem-solving, ensuring readiness for CKA certification and real-world deployment challenges.
Mohan Pothula is an accomplished Enterprise Architect with over 20 years of experience leading digital transformation and AI adoption across financial institutions and large-scale enterprises. He has designed and modernized data platforms at DBS Bank, SPH, and Mediacorp, integrating AWS-based architectures, microservices, and CI/CD automation to support big-data analytics and AI initiatives. His expertise covers cloud migration, data governance, real-time analytics, and secure architecture design aligned with banking and regulatory standards.
Within the AWS Certified Machine Learning Specialty Training, Mohan bridges enterprise data strategy with ML engineering best practices. He guides participants in architecting end-to-end machine learning systems—from data ingestion and model training to deployment on AWS services like S3, SageMaker, Lambda, and Redshift—ensuring solutions are both scalable and compliant for enterprise adoption.
Truman Ng is a certified AI and network engineering professional with a multidisciplinary portfolio spanning machine learning, blockchain, cybersecurity, and automation. A graduate in Electrical and Electronic Engineering from NUS and a PMP®-certified project manager, he holds multiple credentials including Huawei HCIE®, Cisco CCNP, and Certified Bitcoin Professional (CBP). His teaching portfolio covers Python, TensorFlow, Docker, CI/CD pipelines, and RPA systems, reflecting deep competence in both software engineering and IT infrastructure.
Leveraging his cross-domain expertise, Truman connects the Agentic AI Apps curriculum to real-world deployment pipelines—from model orchestration to containerized agent systems. His sessions emphasize modular design, security, and scalability, preparing learners to deploy CrewAI- and Autogen-based applications efficiently across cloud or on-premise environments..
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