— Bay 01: Intake

Engineering Craft for AI Work

Three courses built around the actual work of AI engineering — not sales decks. Learn version control, MLOps pipelines, and prompt design through structured exercises and real practice environments.

+60 3-2145 8726 [email protected] Kuala Lumpur, MY

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Production Bay

Current Course Tickets

Each course is a bounded production run with defined scope, prerequisites, and measurable outputs.

Course 01 7 weeks

Software Fundamentals for AI Engineering

Version control, testing, code reviews, and basic deployment — the surrounding engineering craft that turns an experimental notebook into a reliable system.

Git workflows and branching strategies
Testing patterns for AI-adjacent code
Deployment basics on shared environments

RM 1,480 Enquire

Course 02 10 weeks

MLOps in Practice

Operating machine learning systems in production. Data pipelines, model registries, monitoring, and safe rollout practices covered with hands-on exercises.

Data pipeline architecture
Model registries and versioning
Monitoring and rollout safety

RM 2,780 Enquire

Course 03 3 evenings

Short Introduction to Prompt and Context Design

For professionals working with LLM tools who want to understand prompt design, context curation, and careful output evaluation. No prior ML experience required.

Prompt structure and iteration
Context curation methods
Evaluating outputs with scepticism

RM 260 Enquire

— Dispatch Window

Ready to move from notebooks to production?

Seats are limited to keep cohorts small and feedback meaningful. Write to us or call to discuss which course fits your current stage.

Get in Touch +60 3-2145 8726

Information Bay

Common Questions

Do I need prior AI experience to enrol?

It depends on the course. The Software Fundamentals course is suitable for self-taught developers moving into team contexts — some coding experience is helpful. MLOps in Practice assumes familiarity with Python and basic data concepts. The Prompt and Context Design short course has no machine learning prerequisites at all and is aimed at anyone using LLM tools at work.

How are sessions delivered?

All sessions are online. MLOps in Practice uses shared practice environments for hands-on work. Weekly sessions combine concept walkthroughs with structured exercises. The short Prompt course runs over three evenings at set times to allow group discussion.

What happens at the end of the MLOps course?

Students complete a small MLOps design presentation at the end of the programme. Written peer feedback is included as part of the mentor review process — it is one of the more useful aspects of the programme because you see how others approached similar problems.

Can my employer pay for the course?

Yes. We can issue an invoice addressed to your company. Some learners also explore HRDC claimability — we can provide documentation to support that process. Contact us directly to discuss the specifics for your organisation.

What is the refund policy?

Full refunds are available up to 7 days before a cohort starts, provided you write to us before that date. After the cohort has started, we handle requests on a case-by-case basis. Our terms and conditions page has the full details.

How large are the cohorts?

We keep cohort sizes small — typically 8 to 14 participants — so that feedback is personal and exercises do not get lost in a crowd. When a cohort fills, we open a waitlist for the next run.

Location

Find Our Office

Jalan Sultan Ismail, 50250 Kuala Lumpur

Clock-In Station

Get in Touch

Enquire about a course, ask about prerequisites, or request an invoice for your company.

Contact Details

Phone

+60 3-2145 8726

[email protected]

Address

Jalan Sultan Ismail, 50250 Kuala Lumpur, Malaysia

Working Hours

Monday – Friday: 9:00 AM – 6:00 PM

Saturday: 10:00 AM – 2:00 PM (online only)