Technical Track · 3-Day Weekday Masterclass

In 3 Days, Learn to Build the Data Side of Production AI.

A code-first masterclass on pipelines, retrieval, and privacy for AI systems, taught by an engineer who has handled data in air-gapped environments.

Models get the credit, but data decides the outcome. This masterclass teaches you to feed agents properly, protect personal data, and prove quality with gates.

“He holds the sole-inventor patent for LLM agent systems, granted in 2023, and has spent close to two decades delivering technical training. He has hand-built AI systems for classified environments where the public internet does not exist. In this masterclass, he shares the architecture, his working methods, and the deployment blueprints drawn from completed projects, compressed into 3 days of intensive, hands-on learning.”
Prebook the Data Masterclass

Cohorts of 10 to 25, and seats are running out. Prebooking is free; you pay by invoice only when your cohort is confirmed.

The Model Is Only as Good as the Data You Feed It.

Pipelines Feed the Model

Stale, duplicated, or wrong data flows straight into answers. Retrieval quality is pipeline quality.

PII Everywhere

Personal data runs through most AI workflows, and PDPA penalties now reach 10 per cent of local turnover.

Retrieval That Lies

A vector search that returns plausible-but-wrong documents is worse than no search at all.

No Freshness, No Trust

Nobody measures how old the answers' sources are, so nobody can trust them.

Bootcamp Fatigue

Hundreds of courses, the same recycled content. The trainer sat through them too, and now teaches exactly the part they all skip.

Paper Only

Certificates confirm attendance. The concepts that matter live only in the trainer's head. Here, they live in yours.

Do these sound familiar? Data discipline is the fix behind every good answer.

Yes, Fix the Feeding

The Engineer Who Has Already Hit Every Wall.

The playbook behind every masterclass was bought with years of production attempts and hard failures. The count of the wall is the lesson, and it is the first thing he teaches.

More Than 100 Students in 2026

More than a hundred students in Singapore completed this similar AI training this year. The format is proven with a live audience.

The Patent

The sole-inventor patent for LLM agent systems, granted in 2023. The legal and logical foundation of modern agents.

GPUs Before the Buzzword

18 years of compute on GPUs, back when the field was called HPC, long before AI became a marketing buzzword.

A Trainer for Over Two Decades

Teaching engineers has been the day job for more than twenty years. Training is the craft, not a side engagement.

Air-Gap and Hybrid Infrastructure

25 years across AWS, Azure, GCP, and on-premises bare metal, including air-gapped environments few engineers ever see.

10 to 25 Seats a Cohort

Small cohorts keep the help personal. Seats are running out fast.

Past students say the most valuable part is simple. You get to ask a human who has done a few things successfully before.

Reserve My Data Seat

The Evidence Keeps Piling Up, and It Does Not Wait.

BBC, The Straits Times · Feb 2025

The bank has said it openly

DBS is phasing out about 4,000 contract and temporary roles over three years as AI takes on work previously done by humans.

CNA · Aug 2026

Experience alone is no longer a shield

About 4 in 10 of those affected by the GovTech cuts were officers in their 40s.

Google, Fortune · Apr 2026

The curve is nearly vertical

75 per cent of all new code at Google is now AI-generated, reviewed and approved by engineers.

IBM Institute for Business Value

This hiring cycle, not 2035

40 per cent of the workforce will need reskilling within three years because of AI.

Dark Daily · Oct 2025

The scan doctors got busier, not redundant

AI now helps read CT scans, yet imaging demand grew even faster and radiologist vacancies stayed high. When AI makes something cheaper, the world orders more of it.

BBC, Business reporting · May 2025

The fintech that rehired its humans

Klarna let an AI assistant do the work of 700 service agents, then rehired people when quality slipped. The winners are the humans who can direct the AI.

None of these companies failed. They restructured, and loyalty no longer shields anyone. PwC’s 2026 jobs barometer finds roles professionalised by AI growing twice as fast as the rest. Be the one directing the machines, not the one replaced by them.

Hold My Priority Spot

Three Days. Feed It Right, Protect It, Prove It.

Day Morning Afternoon Focus
Day 1 You learn what models do with your data, then work embeddings and retrieval architecture hands-on. The afternoon covers the ingestion patterns AI workloads actually need, from chunking to metadata design. AI Literacy for Data Teams
Day 2 Secure ingestion comes first, with PII handling, anonymisation, and PDPA duties built into the pipeline. You then build the vector store layer properly, with freshness signals and source provenance on every document. Protect and Serve
Day 3 You add evals for retrieval quality, so wrong sources fail loudly instead of quietly. The capstone is a complete retrieval pipeline with privacy and quality gates, built by you and presented. Prove It

Each day comprises approximately 25% guided sessions, 60% hands-on labs on a real task, and 15% structured reflection. The table above is an example. Actual content includes more practical material than described, may differ slightly as it tracks the latest industry trends, and is refreshed right up to each cohort. The exact setup guide will be shared one week before Day 1.

Before You Arrive

What to bring for the course

  • A laptop that is ready to code, with a good CPU, sufficient memory, and free disk space for the hands-on labs
  • Administrator rights on your login account, because you will install the tools yourself
  • Everyday computer fluency; a developer background helps but is not required
  • A working knowledge of Python and JavaScript to make the labs smoother

What is provided

  • Basic AI credits for the course labs, so there is nothing to purchase beforehand
  • The professional setup guide, shared one week before Day 1

Save My Seat Now

Two Ways to Take the Masterclass.

Standard

An open cohort on the published outline

  • An open cohort of 10 to 25
  • The published 3-day outline, weekday, Mon to Fri
  • All AI credits for the labs, and the setup guide
  • The 30-day follow-up question-and-answer clinic
Prebook Standard

Custom

A private cohort tailored to your organisation

  • A private cohort for your organisation
  • A needs analysis call with the trainer before the course
  • An agenda tailored to your industry, data, and toolchain
  • Labs run on your own documents and codebase
  • A two-week post-course implementation clinic
  • Travel and venue billed separately where applicable
Enquire About Custom

Prebooking is free. You pay by invoice only when your cohort is confirmed.

What You Walk Out With

Retrieval Architecture

An embedding and retrieval design you built and understand.

Privacy-Built Pipelines

Ingestion with PII handling and PDPA duties enforced.

Provenance on Every Answer

Freshness and source tracking that makes answers auditable.

Retrieval Evals

Quality gates that fail loudly when sources go wrong.

Cost Control

Chunking and caching choices that keep the invoice sane.

A Working Pipeline

A complete retrieval pipeline you take back to work.

Walk out with a pipeline you would stake an answer on.

Start Building in 2027

One Foundation. Six Masterclass Families.

The Foundation Course is the shared entry, running every weekend. Each masterclass below runs as a 3-day weekday specialist course, in a Standard open cohort or a Custom private cohort for your organisation.

Technical Track

Manager Track

Leader Track

You bring the domain expertise. We bring the engineering discipline. Good data is the strategy.

Prebook My Seat Now