Three Programmes, One Clear Path
Whether you're starting from scratch or ready to build and deploy production-level models, there's a structured programme that meets you where you are.
← Back to HomeHow Each Programme Is Structured
Every Loopmind programme follows the same core loop: introduce a concept through a practical task, build something that demonstrates it, receive written feedback from a mentor, revise and document. That loop runs every week — with the complexity of what you're building increasing as the programme progresses.
Learn by Doing
Concepts are introduced through small, focused exercises — not long explanatory videos followed by a quiz. You encounter ideas by working with them.
Build and Submit
Each week involves a project submission — code, a trained model, a documented analysis — something concrete that you've made and can describe.
Receive and Refine
Mentors return written feedback on your submission. You refine your approach based on that feedback — and carry the improved understanding into the next iteration.
AI Foundations Programme
A welcoming programme introducing Python, data handling, and the core ideas of machine learning through small, hands-on projects. Suited to those beginning their journey. Runs over eight weeks with live sessions, guided exercises, and mentor feedback.
By the end of the programme, you'll have a starter portfolio project — a working piece of code you built yourself and documented so you can explain what it does and why you made the choices you did.
- Python basics and data handling with Pandas
- Introduction to scikit-learn and core ML concepts
- Weekly live sessions with Q&A (recorded)
- Mentor feedback on each submitted exercise
- Starter portfolio project and completion record
Weekly Flow:
Machine Learning Engineering Track
An intermediate track centred on building and evaluating models with real datasets and everyday tooling. Designed for learners with basic Python who want practical depth. Runs over twelve weeks with structured projects, code reviews, and small-group mentoring.
You'll work with real datasets, evaluate your models rigorously, and produce applied portfolio pieces — documented in a way that demonstrates your engineering reasoning, not just your outputs.
- Model training, validation, and evaluation pipelines
- Working with real, messy datasets from multiple domains
- Code reviews with written mentor observations
- Small-group mentoring sessions per cohort
- Multiple applied portfolio pieces at close
Prerequisites:
Basic Python familiarity — you should be comfortable writing functions, working with lists and dictionaries, and reading error messages. The Foundations Programme or equivalent experience works well as preparation.
Advanced AI Development & Deployment
A full programme covering deep learning, fine-tuning, and careful deployment, with a strong emphasis on real project work and clean engineering. Built for committed learners developing a solid portfolio. Runs over sixteen weeks with a capstone, one-to-one mentoring, and thorough career-preparation practice.
The capstone is a full project you design, build, document, and present — covering the complete lifecycle from problem framing to a deployed output. One-to-one mentoring sessions are included to work through blockers as they arise.
- Deep learning architectures and fine-tuning pre-trained models
- Deployment practices — APIs, containers, monitoring basics
- One-to-one mentoring sessions throughout
- Full capstone project with mentor-guided review
- Career-preparation practice and portfolio review session
Which Programme Suits You?
| Feature | Foundations RM 580 |
ML Engineering RM 2,300 |
Advanced RM 4,600 |
|---|---|---|---|
| Duration | 8 weeks | 12 weeks | 16 weeks |
| Python required | None | Basic | Intermediate |
| Mentor feedback on code | |||
| 1-to-1 mentoring sessions | — | — | |
| Capstone project | — | — | |
| Deployment content | — | Intro | |
| Instalment option | — | ||
| Best for | Complete beginners | Python users wanting ML depth | Building a strong portfolio |
Not sure which to choose? Drop us a message and we'll help you decide.
What Every Programme Shares
Privacy by Default
Learner data is handled in line with Malaysia's PDPA 2010. We collect only what's necessary and don't share it for marketing purposes.
Recorded Live Sessions
All live sessions are recorded and made available to cohort members within 24 hours — so time zones and scheduling conflicts don't create permanent gaps.
Open Source Tooling Only
All programmes use open source tools — Python, scikit-learn, PyTorch, Git. You own the environment you learn in and can continue using it after the programme ends.
Updated Before Each Cohort
Programme materials are reviewed and updated before each cohort starts. Tooling examples stay current; deprecated approaches are replaced.
Cohort Channel Access
Each cohort has a shared discussion channel for the duration of the programme — for peer questions, mentor responses, and shared resources.
Honest Completion Records
Completion records describe what the programme covers. They're not formal qualifications — but they reflect real work you did and can speak to in any context.
Programme Investment
All prices in Malaysian Ringgit. No hidden costs during the programme.
AI Foundations
8 weeks
RM 580
One-time payment
- Live weekly sessions
- Guided exercises
- Mentor feedback
- Starter portfolio project
- Completion record
ML Engineering
12 weeks
RM 2,300
Or instalment available
- Structured project work
- Code reviews
- Small-group mentoring
- Applied portfolio pieces
- Cohort discussion channel
Advanced & Deployment
16 weeks
RM 4,600
Or instalment available
- 1-to-1 mentoring sessions
- Capstone project
- Deployment content
- Portfolio review session
- Career-prep practice
Not Sure Where to Start?
Send us a message with a little about your background and what you're hoping to be able to build. We'll suggest the programme that fits best and answer any questions you have about structure, timing, or cost.
Get in Touch