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Harness and Loop Engineering for AI Agents

Course Information

  • 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.

Skills Framework

TSC Title
Text Analytics and Processing
TSC Code
ICT-DIT-4029-1.1

Funding Validity

Funding for this course is valid from 22 Dec 2021 to 21 Dec 2027. Register and complete the course within this period to qualify for funding support.

Learning Outcomes

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

  • LO1: Identify and develop text analytics solutions using Cross-Industry Standard Process for Data Mining (CRISP-DM).
  • LO2: Read in text corpus and perform text pre-processing.
  • LO3: Perform text analytics and modify the data with feature engineering.
  • LO4: Perform sentimental analysis from social media data.
  • LO5: Perform sentiment summarization and visualization.

Course Brochure

Download Course Brochure

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.
  • 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 - Harness and Loop Engineering for AI Agents

Course Code: TGS-2021010367
  • WSQ
  • SFC
  • PSEA
  • UTAP
  • SFEC
  • Absentee Payroll
  • MCES

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What's This Course About

This course equips participants with practical skills to design reliable harnesses and execution loops for AI agents. Learners will explore how harness engineering combines instructions, context, tools, memory, permissions, validation rules, and evaluation mechanisms to guide agent behaviour and improve the quality of task execution.

Participants will learn to develop structured agent loops that enable AI agents to observe inputs, analyse information, plan actions, use tools, evaluate results, learn from feedback, and retry when required. The course covers loop controls such as stopping conditions, error recovery, state management, human approval, output validation, and performance monitoring to prevent repetitive, unsafe, or unsuccessful agent behaviour.

A key focus is the application of text analytics and text processing within agent harnesses and loops. Learners will prepare, clean, classify, summarise, and extract information from unstructured text such as documents, customer feedback, emails, reports, and online content. They will apply techniques including tokenisation, text normalisation, sentiment analysis, entity extraction, topic identification, semantic search, and text classification to help agents interpret inputs and make informed decisions.

Through hands-on projects, participants will build AI agent workflows that process text, retrieve relevant context, perform multi-step analysis, validate generated outputs, and refine results through iterative feedback loops. Emphasis is placed on reliability, traceability, security, human oversight, and measurable evaluation.

By the end of the course, learners will be able to design and optimise harness and loop engineering solutions that enable AI agents to process text effectively, complete complex tasks consistently, and generate dependable insights for real-world business applications.

WSQ Funding

Full Fee $720.00 Before GST
GST $64.80 9% of fee
Baseline Nett $424.80 SG/PR age 21+ · 50% funded
MCES / SME Nett $280.80 SG age 40+ · 70% funded
SkillsFuture Enterprise Credit (SFEC)

Eligible Singapore-registered companies can tap on $10000 SFEC to cover out-of-pocket expenses.

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 FormSubmit PSEA Form

Course FeeBefore Funding

$720.00 (GST-exclusive)
$784.80 (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: Harness and Loop Engineering for AI Agent Text Analytics

Topic 2: Text Collection, Cleaning and Pre-processing for Agent Workflows

Topic 3: Text Analytics, Information Extraction and Feature Engineering

Topic 4: Sentiment Analysis and Iterative Agent Evaluation Loops

Topic 5: Sentiment Summarisation, Visualisation and Agent Output Optimisation

Assessment

  • Written Exam
  • Practical Exam

Course Info

Promotion Code

Promo or discount cannot be applied to WSQ courses

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.

Minimum Software/Hardware Requirement

Software:

You can download and install the following software:

Hardware: Windows and Mac Laptops

About Progressive Wage Model (PWM)

The Progressive Wage Model (PWM) helps to increase wages of workers through upgrading skills and improving productivity. 

Employers must ensure that their Singapore citizen and PR workers meet the PWM training requirements of attaining at least 1 Workforce Skills Qualification (WSQ) Statement of Attainment, out of the list of approved WSQ training modules.

For more information on PWM, please visit MOM site.

Funding Eligility Criteria

Individual Sponsored Trainee Employer Sponsored Trainee
  • Singapore Citizens or Singapore Permanent Residents of age 21 and above
  • From 1 October 2023, attendance-taking for SWDA's (formerly SSG) funded courses must be done digitally via the Singpass App. This applies to both physical and synchronous e-learning courses.​
  • Trainee must pass all prescribed tests / assessments and attain 100% competency.
  • We reserves the right to claw back the funded amount from trainee if he/she did not meet the eligibility criteria.
  • Singapore Citizens or Singapore Permanent Residents who are DIRECT EMPLOYEE of the sponsoring company.
  • From 1 October 2023, attendance-taking for SWDA's (formerly SSG) funded courses must be done digitally via the Singpass App. This applies to both physical and synchronous e-learning courses.​
  • Trainee must pass all prescribed tests / assessments and attain 100% competency.
  • We reserves the right to claw back the funded amount from the employer if trainee did not meet the eligibility criteria.

 SkillsFuture Credit: 

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

 PSEA:

  • To check for Post-Secondary Education Account (PSEA) eligibility, goto mySkillsFuture portal and search for this course code.
  • Scroll down to "Keyword Tags" to verify for PSEA eligibility.
  • If there is “PSEA” under keyword tags, the course is eligible for PSEA.  
  • And if there is no “PSEA” under keyword tags, the course is ineligible for PSEA. 
  • Not all courses are eligible for PSEA funding.

 Absentee Payroll (AP) Funding: 

  • $4.50 per hour, capped at $100,000 per enterprise per calendar year.
  • AP funding will be computed based on the actual number of training hours attended by the trainee.

 SFEC:

  • If the Training Provider has submitted an enrolment for course fee grant claim in Training Partners Gateway (TPGateway), SWDA would be able to derive SFEC funding based on this record. There is no need for enterprise to submit any claim request and the SFEC claim will be automatically generated and disbursed.
  • Where there is no such record, eligible employers are required to submit an SFEC claim after course completion via the SFEC microsite.
  • SkillsFuture Enterprise Credit (SFEC) Microsite 

 

Steps to Apply Skills Future Claim

  • The staff will send you an invoice with the fee breakdown.
  • Login to the MySkillsFuture portal, select the course you’re enrolling on and enter the course date and schedule.
  • Enter the course fee payable by you (including GST) and enter the amount of credit to claim.
  • Upload your invoice and click ‘Submit’

SkillsFuture Level-Up Program

The  SkillsFuture Level-Up Programme provides greater structural support for mid-career Singaporeans aged 40 years and above to pursue a substantive skills reboot and stay relevant in a changing economy. For more information, visit SkillsFuture Level-Up Programme

Get Additional Course Fee Support Up to $500 under UTAP

The Union Training Assistance Programme (UTAP) is a training benefit provided to NTUC Union Members with an objective of encouraging them to upgrade with skills training. It is provided to minimize the training cost. If you are a NTUC Union Member then you can get 50% funding (capped at $500 per year) under Union Training Assistance Programme (UTAP).

For more information visit NTUC U Portal – Union Training Assistance Program (UTAP)

Steps to Apply UTAP

  • Log in to your U Portal account to submit your UTAP application upon completion of the course.

Note

  • SWDA subsidy is available for Singapore Citizens, Permanent Residents, and Corporates.
  • All Singaporeans aged 25 and above can use their SkillsFuture Credit to pay. For more details, visit www.skillsfuture.gov.sg/credit
  • An unfunded course fee can be claimed via SkillsFuture Credit or paid in cash.
  • UTAP funding for NTUC Union Members is capped at $250 for 39 years and below and at $500 for 40 years and above.
  • UTAP support amount will be paid to training provider first and claimed after end of class by learner.

Appeal Process

  1. The candidate has the right to disagree with the assessment decision made by the assessor.
  2. When giving feedback to the candidate, the assessor must check with the candidate if he agrees with the assessment outcome.
  3. If the candidate agrees with the assessment outcome, the assessor & the candidate must sign the Assessment Summary Record.
  4. If the candidate disagrees with the assessment outcome, he/she should not sign in the Assessment Summary Record.
  5. If the candidate intends to appeal the decision, he/she should first discuss the matter with the assessor/assessment manager.
  6. If the candidate is still not satisfied with the decision, the candidate must notify the assessor of the decision to appeal. The assessor will reflect the candidate’s intention in the Feedback Section of the Assessment Summary Record.
  7. The assessor will notify the assessor manager about the candidate’s intention to lodge an appeal.
  8. The candidate must lodge the appeal within 7 days, giving reasons for appeal 
  9. The assessor can help the candidate with writing and lodging the appeal.
  10. he assessment manager will collect information from the candidate & assessor and give a final decision.
  11. A record of the appeal and any subsequent actions and findings will be made.
  12. An Assessment Appeal Panel will be formed to review and give a decision.
  13. The outcome of the appeal will be made known to the candidate within 2 weeks from the date the appeal was lodged.
  14. The decision of the Assessment Appeal Panel is final and no further appeal will be entertained.
  15. Please click the link below to fill up the Candidates Appeal Form.

Job Roles

Job Roles

  • AI Engineer
  • AI Agent Developer
  • Automation Engineer
  • Machine Learning Engineer
  • Data Scientist
  • Natural Language Processing Engineer
  • Conversational AI Developer
  • Solutions Architect (AI systems)
  • Business Process Automation Analyst
  • Knowledge Management Specialist
  • Customer Experience Analyst
  • Digital Transformation Specialist
  • Product Manager (AI products)
  • AI Quality and Evaluation Engineer
  • AI Governance and Risk Analyst

Trainers

Trainers

Dwight Nuwan Fonseka is Head of Data Science at Plano Pte. Ltd. and an ACLP-certified trainer with deep expertise in data analytics, machine learning, and AI applications. He has extensive hands-on experience developing predictive models, RShiny dashboards, and deep learning solutions using R, Python, TensorFlow, and Keras. With a strong professional background in healthcare, finance, and customer analytics, Dwight brings an applied perspective to teaching AI, focusing on both the opportunities and risks of emerging technologies.

Dr. Alvin Ang is an ACLP-certified trainer with a Ph.D. in Operations Research from Nanyang Technological University and a strong track record in data science, machine learning, and text analytics. He has taught extensively at universities and training institutions, delivering courses in R, Python, data visualization, and advanced analytics. His IBM and Kaggle certifications, along with published research in analytics and optimization, underscore his academic and applied expertise.
In his Harness and Loop Engineering for AI Agents courses, Alvin focuses on both the theoretical underpinnings and hands-on practice. He trains learners to structure agent loops for text preprocessing, information extraction, and output validation, applying methods such as sentiment analysis and NLP. His teaching approach balances analytical rigor with practical case studies, enabling learners to apply agent harnesses effectively in business, research, and digital transformation contexts.

Terence Ee is an experienced IT leader and consultant with more than 25 years of expertise in technology management, information systems, and digital transformation. He has served as Chief Information Officer at the Supreme Court of Singapore and Vice President of Information Systems at Senoko Energy, where he led major IT modernization projects. Since 2017, he has worked as an independent consultant and ACLP-certified trainer, specializing in guiding SMEs and enterprises in adopting future-ready digital platforms. As a WSQ-accredited trainer, Terence delivers programs in digital collaboration, IT governance, and productivity tools. His facilitation emphasizes case studies, simulations, and hands-on practice, enabling learners to apply modern IT systems such as Microsoft 365 and Google Workspace to improve collaboration and business efficiency. With his leadership background and deep IT expertise, Terence prepares learners to thrive in digitally transforming environments.
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.
is a results-driven data scientist and financial services professional with over two decades of experience in data analytics, visualization, and business intelligence. As a Senior Partner and Lead Data Scientist at Big Data Venture Capital, he has led consulting projects, curriculum development, and training operations for blue-chip firms, equipping professionals with practical skills in Microsoft Power BI, Python, and advanced data analytics. His expertise in data acquisition, cleaning, feature engineering, ETL, and visualization ensures that organizations can harness Power BI to transform raw data into actionable insights for strategic decision-making. In addition to his industry leadership, Mr. Peh is a certified adult educator with the WSQ Advanced Certificate in Learning and Performance (ACLP) and has delivered numerous Power BI and data science courses through NTUC LearningHub and other training providers. His ability to merge technical expertise with pedagogy has made him a trusted trainer, empowering professionals to build interactive dashboards, automate reporting workflows, and adopt data-driven cultures. With a unique blend of hands-on technical mastery and proven teaching experience, Mr. Peh has established himself as a credible authority in Power BI and business intelligence solutions

Review

Customer Reviews (2)

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. (Posted on 7/20/2023)
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