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Operationalizing Machine Learning and Generative AI Solutions (AI-300)

Course Information

  • Sessions 4 days
  • Duration 32 hrs
  • Level Intermediate
  • Assessment 1 hr

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.

CASL Skills

  • Prompt Engineering
  • Generative AI Model Evaluation

Funding Validity

Funding for this course is valid from 16 Oct 2026 to 15 Oct 2028. Register and complete the course within this period to qualify for funding support.

Learning Outcomes

  • Learners will create nuanced and strategic prompts that optimise AI model performance, combining different methodologies to generate innovative and effective prompts, and will create prompt variants and compare their performance.
  • Learners will assess the quality, performance and potential impact of generative AI models across the applications deployed, implementing groundedness, relevance, coherence and fluency metrics together with risk and safety evaluations.
  • Participants will explain the architecture of a Machine Learning workspace, the datastores, compute targets and assets it holds, and the identity and access model that governs it.
  • Participants will implement infrastructure as code for Machine Learning using Bicep, the Azure command line interface and GitHub Actions workflows, and manage source control for machine learning projects.
  • Participants will orchestrate model training with MLflow experiment tracking, automated machine learning, hyperparameter tuning and training pipelines.
  • Participants will register, version, deploy and monitor models in production, using real-time and batch endpoints, progressive rollout, drift detection and retraining triggers.
  • Participants will configure Foundry project environments, deploy foundation models to serverless and managed compute endpoints, and implement version control for prompts using Git repositories.
  • Participants will implement observability for generative AI applications and determine optimisation strategies for retrieval-augmented generation and fine-tuned models.

Certification

  • 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.

Microsoft Learning Partner

We are an Authorised Microsoft Learning Partner (Org ID: 5238476). To get the official Microsoft certification, please register your certification exam at a Pearson VUE test center.

Certification Exam

We are Authorised Pearson Vue Testing Center. Once you have prepared for the exam, you can register for the certification here. The course fee does not include the certification exam fee.

You can purchase the exam voucher (one of the lowest prices in Singapore) at Microsoft Role-Based Certification Exam Voucher.

CASL - Operationalizing Machine Learning and Generative AI Solutions (AI-300)

Course Code: TGS-2026066878
  • CASL
  • SFEC
  • Absentee Payroll
  • MCES

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What's This Course About

This course equips learners with the practical skills to operationalise machine learning and generative AI solutions on Microsoft Azure, aligned with the competencies assessed in the Operationalizing Machine Learning and Generative AI Solutions (AI-300) certification.

Two capabilities run through the course. Learners will create nuanced and strategic prompts that optimise AI model performance, combining different methodologies to generate innovative and effective prompts, and will create prompt variants and compare their performance across a workload. Learners will also assess the quality, performance and potential impact of generative AI models across the domains and applications an organisation deploys, applying groundedness, relevance, coherence and fluency metrics together with risk and safety evaluation.

The course covers the Machine Learning workspace, its datastores, compute targets, data assets, environments and components; infrastructure as code using Bicep, the Azure command line interface and GitHub Actions; experiment tracking with MLflow, automated machine learning, hyperparameter tuning and training pipelines; model registration, versioning, real-time and batch endpoints, progressive rollout and safe rollback; data drift detection and retraining triggers; Foundry project environments, foundation model deployment and provisioned throughput; evaluation, observability, logging and cost tracking; and the optimisation of retrieval-augmented generation and fine-tuned models.

Designed for intermediate learners, this course suits machine learning engineers, MLOps and DevOps engineers, data scientists, AI engineers, cloud engineers and solution architects. A working knowledge of Python, Azure fundamentals and machine learning concepts is recommended.

Bonus: Free Practice Exams

Get exam-ready on our Practice Exam Portal — train in realistic Practice Mode and timed Exam Mode, then retake them as many times as you like before the real exam.

Start Practising →

CASL Funding

Full Fee $2,000.00 Before GST
GST $180.00 9% of fee
Baseline Nett $1,180.00 SG/PR age 21+ · 50% funded
MCES / SME Nett $780.00 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

Course FeeBefore Funding

$2,000.00 (GST-exclusive)
$2,180.00 (GST-inclusive)

Course Date

* Required Fields

Additional Note

Please bring your own laptop for hands-on training. If you don't have laptop, we can provide spare laptop for training use.

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.

Cancellation & Reschedule Policy

  • 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

Course Details

What You'll Learn

Topic 1: Design and Implement an MLOps Infrastructure

Topic 2: Implement Machine Learning Model Lifecycle and Operations

Topic 3: Design and Implement a GenAIOps Infrastructure

Topic 4: Implement Generative AI Quality Assurance and Observability

Topic 5: Optimize Generative AI Systems and Model Performance

Assessment

  • Case Study

Course Info

Minimum Entry Requirement

Knowledge and Skills

  • Able to operate using computer functions
  • 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: 21-65 years old

Minimum Software/Hardware Requirement

Software: Latest web browser (Google Chrome or Microsoft Edge) with internet access.

Hardware: Windows or Mac Laptops

SkillsFuture Credit

  • Eligible Singapore Citizens can use their SkillsFuture Credit to offset the course fee payable after funding.

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.

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.
  1. Check your company's SFEC eligibility and balance on EnterpriseSG.
  2. 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.
  3. Your employee attends and completes the course. We submit the attendance and assessment results to SWDA.
  4. 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.

Appeal Process

If you disagree with an assessment decision, you have the right to appeal.

  1. 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.
  2. Discuss the decision with the assessor or the assessment manager first.
  3. 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.
  4. Lodge your appeal within 7 days, giving your reasons, using the Candidate Appeal Form. The assessor can help you write and lodge it.
  5. 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.
  6. You will be told the outcome within 2 weeks of lodging the appeal. The panel's decision is final.

Job Roles

Job Roles

  • Machine Learning Engineers
  • MLOps and DevOps Engineers
  • Data Scientists
  • AI Engineers
  • Cloud Engineers
  • Solution Architects

Trainers

Trainers

Sanjiv i is an ACTA certified experienced leader with a proven track record in business / finance consulting and in developing i) business intelligence (BI) solutions ii) data analytics/analysis solutions and iii) IOT lead BI solutions. Sanjiv's goal through Prudentia Consulting, is to promote the simple joy and excitement of actively using the Microsoft Platform. He believes that the agility afforded by the Microsoft platform helps businesses get time back for deeper business thinking and to spend more time with their end customers Sanjiv has rich experiences in diverse/complex high-tech businesses, turn around environments and strategic transformations. His functional expertise is in sales analytics, financial planning and analysis, engineering and program management. He has worked across discrete manufacturing, professional services and higher education verticals. He also has a working knowledge of equities portfolio management within the financial services domain.Sanjiv is the CEO of Prudentia Consulting, an organization committed to promoting the active usage of the Microsoft Platform. Prior to this, he has worked at Microsoft (US & APAC: 9.2 years), Cognizant Tech Solutions (3.3 years), Yazaki North America (8 years) and until recently at Oracle. Here are a few of his BI/analytics projects driven at scale: Built APAC wide BI dashboard using the Power BI umbrella tool set (Power BI online, Power BI desktop and Power Pivot) and a KPI lake (SQL DB), Helped develop key KPIs – identified key KPIs and helped land this in the DB, Developed a budget audit tool that captured budget inputs from a host of countries across the globe, Developed a business unit P&L reporting tool (functional architecture) in Business Objects for the world-wide financial planning and analysis team.

Alec Tan is a ACTA certified trainer, He has a number of Comptia certifications. Since 2002, starting off from IT technical background to pre-sales, sales account manager, system integration, operate IT retail / repair shop business in Sim Lim Square 2008 ~ 2012, and back to IT industry employment, freelance IT Trainer till present.

Kishan Raaj is a seasoned Data Science and SAP Program Manager with over 15 years of experience, currently leading all end-to-end training and projects for Data Science across Asia at LITHAN, Singapore. With expertise in machine learning, data analytics, and cloud technologies, he is well-versed in techniques such as regression, decision trees, clustering, and text mining. He has hands-on experience with tools like Python, R, Tableau, PowerBI, and Microsoft Azure Machine Learning Studio.As an ACTA certified trainer, Kishan has designed and delivered comprehensive courses for SAP and Data Science programs, managing teams and training in multiple countries, including Singapore, Malaysia, China, India, and Vietnam. His background in SAP, particularly in S4/HANA and ABAP, combined with his expertise in machine learning libraries such as TensorFlow and Keras, positions him as a highly capable leader in technical education and project management across various industries.

CY Quah is an ACLP-certified trainer and data science professional with extensive experience in Python, NLP, and machine learning. He has led AI training programs for SAP, Temasek Polytechnic, and IMDA under the SGUnited Mid-Career Pathways initiative, and has delivered corporate workshops on text analytics, recommender systems, and chatbot development. His expertise includes applying NLP tools such as NLTK, spaCy, and Gensim for sentiment analysis, topic modeling, and text classification.
Peter Cheong is an IT and knowledge management professional with strong expertise in networking, cybersecurity, and information systems. He has completed the Cisco Networking Academy Introduction to Packet Tracer course and has participated in international ICT and knowledge management conferences such as the IFLA Knowledge Management Satellite Meeting. With professional experience in IT systems and infrastructure, Peter brings both technical knowledge and global exposure to his training. As an adult educator, Peter focuses on building learners’ foundational skills in cybersecurity, network defense, and risk management aligned to CompTIA Security+ objectives. His sessions emphasize real-world security scenarios, equipping participants to recognize vulnerabilities, manage threats, and implement effective security controls. His combination of practical training and industry exposure ensures learners are well-prepared for both the certification exam and workplace application.

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