Our programmes
Three tracks. One connected path.
Each programme is a standalone learning experience — and a step in a carefully connected sequence from first-time coder to neural network practitioner.
← Back to Home― How we teach ―
A methodology built around steady cultivation
Each track at Suria Code follows the same underlying structure: concept introduction, guided practice, independent application, and review. The pace is set to allow the first three to happen properly before the fourth, rather than rushing to review something that hasn't been absorbed yet.
Live clinics give learners a weekly checkpoint to surface confusion before it compounds. Recorded materials let them revisit anything that didn't land fully the first time. Peer channels mean the learning continues between sessions without requiring instructor availability.
Projects are not an afterthought — they are the point. Each week's material builds directly toward the track's capstone. By the time you reach the final project, you have already used most of the skills it requires in smaller exercises.
Concept first
Each topic is introduced with enough context to make sense, not just as a function to memorise.
Guided practice
Exercises are structured so learners can check their understanding with the material at hand.
Independent work
Open-ended tasks where learners apply what they know without a template to follow exactly.
Mentor review
Written feedback from a person who has read your actual work, not a rubric applied automatically.
Beginning with AI and Python
A gentle programme for those planting their first seeds in the field. Over six weeks you learn Python basics, simple data work, and how a model learns from examples, with a relaxed weekly clinic for questions. The garden pace keeps things calm and clear. You finish with a small project and a plan for what to grow next.
- Python fundamentals: variables, loops, functions, files
- Introduction to pandas and basic data handling
- How machine learning models learn from labelled data
- Weekly live clinic for questions throughout the track
- Small capstone project with mentor review
How it unfolds
- 1Environment setup and Python foundations (weeks 1–2)
- 2Data structures, files, and basic pandas (weeks 3–4)
- 3Intro to model training and capstone project (weeks 5–6)
RM 970
Enquire About Track 01Hands-On Machine Learning
A practical track for learners ready to cultivate real skills. Across eleven weeks you practise the full workflow from data to evaluation, completing two grounded projects with personal mentor feedback. Small cohorts mean your questions get attention. Recordings, exercises, and a friendly peer space are included.
- Full ML workflow: data preparation through model evaluation
- scikit-learn in depth: pipelines, cross-validation, tuning
- Two graded projects with written mentor feedback each
- Peer learning community throughout the cohort
- Recommended for Track 01 completers or those with Python experience
How it unfolds
- 1Data handling and exploratory analysis (weeks 1–3)
- 2Model types, training, and evaluation (weeks 4–7)
- 3Project one: classification task with mentor review (week 8)
- 4Pipelines, tuning, and project two (weeks 9–11)
RM 1,440
Enquire About Track 02
Deep Learning Cultivation
An advanced track for developers ready to nurture neural networks across vision and language. Over thirteen weeks you study architectures, training methods, and careful deployment, building a capstone shaped with guidance. The small group keeps mentoring close and feedback thoughtful. Lasting access and a quiet alumni garden support you afterwards.
- Neural network foundations and PyTorch
- Computer vision pipeline: CNNs and image classification
- Natural language processing with transformers
- Deployment: serving and monitoring a model in production
- Lasting alumni garden access after completion
How it unfolds
- 1Foundations: tensors, gradients, training loops (weeks 1–3)
- 2Computer vision module with CNN architectures (weeks 4–6)
- 3NLP module with sequence models and transformers (weeks 7–10)
- 4Capstone project and deployment workshop (weeks 11–13)
RM 1,850
Enquire About Track 03― Which track fits? ―
Side-by-side comparison
| Feature | Track 01 RM 970 · 6 wk |
Track 02 RM 1,440 · 11 wk |
Track 03 RM 1,850 · 13 wk |
|---|---|---|---|
| Prior coding needed | None | Python basics | ML experience |
| Live weekly clinic | |||
| Mentor-reviewed projects | 1 | 2 | 1 capstone |
| Peer community | |||
| Alumni garden access | |||
| Best for | First-time coders & career explorers | Developers adding data skills | Engineers going deeper into AI |
― Shared across all tracks ―
Standards that apply to every programme
Privacy and data care
Learner data is handled under PDPA 2010 requirements. Exercise datasets used in the programmes do not include personal information.
Six-month content review
Library versions, tools, and exercises are reviewed every six months. Significant changes in Python or ML tooling are reflected in the syllabus before the next intake.
Three-day feedback commitment
Project submissions receive written mentor notes within three working days. This is a schedule we plan around, not a best-effort promise.
Open-source toolchain
All tools taught across the three tracks are free, open-source, and widely used outside of our programmes. No vendor dependency is introduced.
Cohort size limit
No cohort exceeds fifteen learners. This limit is not adjusted based on demand — it exists to protect the quality of mentoring and clinic time.
HRDCorp claimable
Eligible Malaysian employees may claim programme fees through HRDCorp. Documentation is provided on enrolment for claims processing.
― Pricing ―
What each track costs
All fees include course materials, recording access, weekly clinic, project feedback, and the peer community. No add-ons.
Beginning with AI & Python
RM 970
6-week programme
- All recorded lessons
- Weekly live clinic
- Capstone project + feedback
- Peer community access
Hands-On Machine Learning
RM 1,440
11-week programme
- All recorded lessons
- Weekly live clinic
- Two projects + mentor feedback
- Peer community access
Deep Learning Cultivation
RM 1,850
13-week programme
- All recorded lessons
- Weekly live clinic
- Capstone project + feedback
- Lasting alumni garden access
― Ready to choose? ―
Not sure which track to start with?
Send us a note with a little about your background. We will suggest the most suitable starting point and tell you what to expect from the first few weeks.
Get Advice on Your Track