AI Development Tracks for Every Stage of the Journey
From writing your first Python script to deploying neural networks — Nadi Tech's three tracks connect into a complete development path.
Back to HomeHow the Tracks Are Built
Each track follows the same structural logic — a deliberate pace, project work, live clinics, and clear criteria for moving forward. The content deepens; the support model stays consistent.
Structured Lessons
Each week covers a defined topic with reading material, worked examples, and a short exercise to apply it.
Weekly Open Clinic
A live session each week where you can bring questions, share code, and hear how others are working through similar challenges.
Project Work
Every track includes one or more projects that you build from scratch, with written feedback from your instructor.
Forward Recommendation
At the close of each track, you receive a clear recommendation about where to go next — or whether to take some time before continuing.
Introduction to AI Building
A gentle gathering point for newcomers. Over six weeks you learn Python basics, simple data handling, and how a model is trained, with a weekly clinic where questions are welcome. The pavilion pace keeps things calm. You finish with a small project and a clear next step.
What You Cover
- Python foundations — variables, functions, loops, file handling
- Handling data with NumPy and Pandas
- What a model is and how it learns from data
- A small, complete project you build yourself
Track Steps
Enrol and receive your first week's materials and clinic schedule
Work through weekly lessons and attend or watch the clinic session
Submit your project in week six and receive written feedback
Receive your certificate and a recommendation for the next track
Best for
People with no coding background who want to understand what AI development involves before committing to a longer track.
Best for
Developers comfortable with Python who want to build, train, and evaluate models — and do it in a cohort where they can compare notes with others at the same stage.
Machine Learning Workshop
A practical track for learners ready to build together. Across ten weeks you cover data work, training, and evaluation, completing two grounded projects with personal feedback. Small cohorts keep mentoring close. Recordings and a supportive peer space are included.
What You Cover
- Data preparation — cleaning, feature engineering, pipelines
- Supervised and unsupervised learning with scikit-learn
- Evaluation metrics and model selection decisions
- Two complete projects with personal written feedback
Track Steps
Enrol, meet your cohort in the peer space, and receive week one material
Progress through lessons with the clinic each week as your anchor point
Submit Project 1 at week five and Project 2 at week ten; receive written notes on both
Receive certificate and a forward recommendation at completion
Deep Learning Pavilion
An advanced track for developers ready to study neural networks in depth. Over thirteen weeks you cover architectures, training, and deployment, building a capstone with guidance. The close cohort keeps feedback thorough. Lasting access and a quiet alumni shelter support you afterwards.
What You Cover
- Neural network architectures — feedforward, CNN, RNN, Transformer basics
- Training dynamics — loss functions, optimisers, regularisation
- Model packaging and deployment patterns
- Capstone project with instructor guidance throughout
- Lasting recording access and alumni community after completion
Track Steps
Enrol, set up your environment, and begin week one on neural network foundations
Progress through architectures and training concepts, attending weekly clinics
Propose and build your capstone from week nine with instructor check-ins
Submit final capstone, receive certificate, and join the alumni shelter
Best for
Developers who have completed the Machine Learning Workshop or have equivalent experience and want to go deeper into architectures, training, and deployment.
Choosing the Right Track
Compare what each track includes to decide where to start.
| Feature | Intro Track | ML Workshop | Deep Learning |
|---|---|---|---|
| Duration | 6 weeks | 10 weeks | 13 weeks |
| Price (RM) | 950 | 1,420 | 1,830 |
| Weekly clinic | |||
| Number of projects | 1 | 2 | 1 capstone |
| Written instructor feedback | |||
| Recording access after track | During track | During track | Lasting access |
| Alumni community | — | — |
Standards Across All Tracks
These practices apply regardless of which track you join.
Data & Privacy
Student data is handled in line with Malaysian PDPA standards. Nothing is shared with third parties for marketing.
Curriculum Review
Each track is reviewed before every new intake. Changes are made when the field has genuinely shifted, not on an arbitrary schedule.
Cohort Limits
We cap at 14 participants per intake. If a track is full, we will tell you and offer a place in the next one.
Certificates
Issued by Nadi Tech upon project submission and completion — a concrete record of the work completed.
Clinic Recordings
Every weekly clinic is recorded. Access is included for the duration of each track (and beyond for Pavilion students).
Instructor Contact
Direct email access to your instructor throughout the track for questions that cannot wait until the next clinic.
Track Fees
All fees quoted in Malaysian Ringgit. No subscriptions, no add-ons.
Introductory
Introduction to AI
RM 950
6 weeks · 1 project
- Weekly clinic (live + recorded)
- Written project feedback
- Completion certificate
- Peer discussion space
Most Popular
ML Workshop
RM 1,420
10 weeks · 2 projects
- Weekly clinic (live + recorded)
- Written feedback on both projects
- Completion certificate
- Peer discussion space
Advanced
Deep Learning Pavilion
RM 1,830
13 weeks · capstone
- Weekly clinic (live + recorded)
- Thorough capstone feedback
- Lasting recording access
- Alumni community access
Not sure which track fits?
Write to us and we will talk through your background and what you are hoping to build. We will suggest the most sensible starting point.
Get a Recommendation