Courses
Three courses, three depths of study
Each course is complete in itself. You choose the one that fits where you are now, not where you'd like to be in five years.
Back to HomeOur Method
How the studio works
Aim
Each course begins with a clear statement of what you'll be able to do by the end. Not a credential — a set of real capabilities tied to the projects you complete.
Method
You receive reading and structured tasks each week. You submit work. A teacher reads it and writes a response. You revise and move on. This loop runs throughout the course.
Work
The output of each course is a set of real projects — small, complete, and honest about what they demonstrate. Not exercises, not mock assessments, but work you built from scratch.
Course 01
Studio Foundations
RM 480 · 6 weeks
A short course covering the practical foundations of AI work: how data becomes a model, how models are evaluated, and how small projects are structured from first sketch to final report. Six weeks, with weekly tasks and written feedback. Aimed at learners with general programming familiarity who would like to begin a careful first season of study.
- The data pipeline from raw input to model output
- Model evaluation: what the numbers mean and what they don't
- Structuring a project from initial question to written report
- Weekly written feedback from the course teacher
- Final deliverable: a structured project report
Process Steps
- 01 Orientation: tools, environment, and course structure
- 02 Data collection, cleaning, and exploration
- 03 Model selection and initial training
- 04 Evaluation: metrics, tests, and interpretation
- 05 Iteration and refinement with teacher feedback
- 06 Final project report and course close
Who this is for
Learners with general programming experience in Python who have not yet worked through an AI or machine learning problem from start to finish. You don't need to have studied data science or statistics. The course introduces those ideas as part of the project work.
Who this is for
Those who have completed an introductory course in machine learning or AI, or who have similar working experience. If you've trained models but haven't had a teacher review your evaluation approach, this is the right next step.
Course 02
Studio Practice Course
RM 1,140 · 12 weeks
A focused course in which learners build and evaluate practical machine-learning projects under the quiet supervision of a working teacher. Twelve weeks, with weekly live sessions and self-paced project work. Aimed at those who have completed a first introductory course or have similar working experience.
- Building practical ML projects from defined problem to evaluated model
- Weekly live sessions with the course teacher
- Self-paced project work alongside sessions
- Written feedback on all submissions throughout
- Two to three completed project pieces by end of course
Process Steps
- 01–02 Problem framing and dataset selection
- 03–05 Exploratory analysis and feature engineering
- 06–08 Model development and comparison
- 09–10 Evaluation rigour and error analysis
- 11–12 Project documentation and course close
Course 03
Long-form Studio Programme
RM 1,950 · 20 weeks
A long-running studio programme for those who wish to develop a fuller AI practice over several months, including data engineering, model design, evaluation, and the careful deployment of models. Twenty weeks, with structured written feedback at every stage and a final portfolio review by a senior teacher.
- Data engineering: pipelines, storage, and data quality
- Model design: architecture choices and their trade-offs
- Rigorous evaluation and model interpretability
- Careful model deployment and monitoring considerations
- Final portfolio review by a senior teacher
- Two-instalment payment option available
Phase Overview
- Weeks 01–05 Data engineering and pipeline construction
- Weeks 06–10 Model design, selection, and first builds
- Weeks 11–14 Evaluation depth and refinement cycles
- Weeks 15–18 Deployment considerations and integration
- Weeks 19–20 Portfolio assembly and senior review
Who this is for
Those who have already worked through the Studio Practice course or equivalent experience, and want to develop a fuller, more independent AI practice over several months. This is a substantial time commitment — roughly ten to twelve hours per week — and is suited to those who are ready to treat it as a sustained study period.
Choose Your Course
Side by side
A direct comparison to help you decide. If you're still unsure, write to us — we'll suggest the right starting point.
| Feature | Foundations | Practice | Long-form |
|---|---|---|---|
| Duration | 6 weeks | 12 weeks | 20 weeks |
| Price | RM 480 | RM 1,140 | RM 1,950 |
| Weekly live sessions | — | ||
| Written feedback on submissions | |||
| Data engineering module | — | — | |
| Deployment and monitoring | — | — | |
| Senior portfolio review | — | — | |
| Instalment payment option | — | — |
Foundations is best for:
Learners starting their first structured AI project after general programming study.
Practice is best for:
Those with introductory experience who want structured supervision and feedback on real project work.
Long-form is best for:
Those ready to commit several months to developing a fuller, more independent AI practice.
Standards
What applies across all courses
Student Data Privacy
Your submitted work is private. It is not shared publicly or used for any purpose outside course administration.
Practitioner-Written Curriculum
Materials are written by teachers who work in the field. Each course is reviewed and updated before every intake.
Response Within 24 Hours
Submissions are acknowledged within 24 hours. Written feedback is provided within five working days of the submission deadline.
Cohort Cap of 16
No intake runs larger than sixteen students. If a course is full, we will let you know when the next intake opens.
Pricing
Transparent pricing, no hidden fees
All prices are in Malaysian ringgit. The course fee covers materials, sessions, recordings, and written feedback throughout.
6 weeks
Studio Foundations
RM 480
One payment, paid before intake begins
- Course materials and reading
- Weekly tasks and submissions
- Written feedback on all submissions
- Course forum access
12 weeks
Studio Practice
RM 1,140
One payment, paid before intake begins
- Everything in Foundations
- Weekly live sessions (recorded)
- Self-paced project work
- 2–3 completed project pieces
20 weeks
Long-form Programme
RM 1,950
Full payment or two instalments (on request)
- Everything in Practice
- Data engineering module
- Deployment and monitoring
- Senior portfolio review
Next Step
Not sure which course fits?
Write to us with a short note about your background and what you'd like to work toward. We'll suggest the right course and let you know when the next intake opens.
Get in Touch