# cell 01 — programmes

Three Programmes. Three Starting Points.

Each programme is sized to what it actually covers. Choose the one that matches where you are now, not where you hope to be.

← Back to Home

# cell 02 — how we teach

The teaching approach behind all three programmes

All Tunas Nusantara programmes are delivered as computational notebooks — the same format learners will work in when they leave the programme and start using these skills in practice. This is a deliberate choice rather than a stylistic one: seeing material in the working format sets more accurate expectations about what the work actually involves.

Each programme has a published prerequisites cell at the top of its description. This is the actual technical bar, stated plainly. A learner can compare their current knowledge against it before making any payment. The entry check for the Machine Learning programme is a short technical assessment to make sure both parties are working from the same understanding of what "comfortable with Python and basic statistics" means in practice.

Live sessions run twice a week in the evening, Malaysian time, so that employed learners do not need to take time off work. All sessions are recorded and available the same evening. Between sessions, there is an open help channel where instructors respond to questions within one working day.

4 weeks

Python for AI Work

10 weeks

Deep Learning Foundations

16 weeks

Applied Machine Learning

# cell 03 — programme 01

Introduction to Python for AI Work

RM 125 · 4 weeks · ~4 hrs/week

A four-week starting module covering the Python a learner actually needs for data and model work: data structures, functions, working with arrays and dataframes, and reading other people's code without fear. Written for career changers coming from non-technical backgrounds, with each concept introduced through a small worked example rather than abstract exercises. Four hours a week, with an open help channel and weekly office hours. Learners who find it is not for them may withdraw in the first two weeks.

What the programme covers

Data structures: lists, dictionaries, tuples and when to use each

Writing and using functions; reading functions written by others

Working with NumPy arrays and Pandas dataframes in practice

Reading and navigating unfamiliar codebases with confidence

Weeks at a glance

Data types, structures and control flow with worked examples

Functions, modules and reading others' code

Arrays and dataframes — the tools you need for data work

Putting it together: a small end-to-end data exercise

prerequisites

No prior programming experience required. A willingness to work through exercises that do not always go right the first time.

Enquire About This Programme

# cell 04 — programme 02

Deep Learning and Neural Network Foundations

RM 370 · 10 weeks · 6–8 hrs/week

A ten-week module on network architectures, backpropagation, regularisation, transfer learning and the practicalities of training on modest hardware, including the use of free and low-cost cloud tiers available to learners in Malaysia. Includes a mentor review of each learner's training runs and a short written report on where their models are underperforming and why. Six to eight hours a week. Learners may repeat the module once at no further charge if they need more time.

What the programme covers

Network architectures: feedforward, convolutional, recurrent

Backpropagation and gradient descent, explained from first principles

Regularisation techniques and how to diagnose overfitting

Transfer learning and fine-tuning pre-trained models

Free and low-cost cloud GPU options available from Malaysia

prerequisites

Comfortable with Python, NumPy and basic calculus (partial derivatives). Prior exposure to supervised learning is helpful but not required.

Enquire About This Programme

# cell 05 — programme 03

Applied Machine Learning Programme

RM 650 · 16 weeks · ~10 hrs/week

A sixteen-week part-time programme covering supervised and unsupervised learning, feature engineering, model evaluation and the practical business of getting a model into a working service. Delivered as weekly recorded material with two live sessions a week held in the evening, Malaysian time. Learners build four projects on real datasets and receive written feedback on each. Suited to those already comfortable with Python and basic statistics; the entry check is published in full so applicants can assess themselves honestly. Around ten hours a week is realistic.

What the programme covers

Supervised learning: regression, classification, ensemble methods

Unsupervised learning: clustering, dimensionality reduction

Feature engineering and selection on real, messy datasets

Model evaluation: metrics, cross-validation, avoiding leakage

Deploying a model into a working service — end to end

Project deliverables

Classification project with real tabular data

Regression project with feature engineering focus

Unsupervised analysis and presentation of findings

End-to-end deployment of a working prediction service

prerequisites

Comfortable with Python and basic statistics (mean, variance, probability basics). Entry check published in full on the programme page. If you have completed the Python module here, you will have the programming foundation needed.

Enquire About This Programme

# cell 06 — which programme

Choosing the right starting point

Feature	Python Intro	Deep Learning	Applied ML ★
Price	RM 125	RM 370	RM 650
Duration	4 weeks	10 weeks	16 weeks
Weekly hours	~4 hrs	6–8 hrs	~10 hrs
Written feedback	✓	✓	✓
Real datasets	—	✓	✓
Live sessions (evening)	Office hours	✓	✓ ×2/week
Mentor training run review	—	✓	—
Free module repeat	—	✓	—
2-week withdrawal option	✓	—	—
Best for	No coding background; testing if programming is the right next step	Python-comfortable; wants to understand how neural networks actually work	Python + stats ready; wants to build and deploy real ML projects ★ Most popular

# cell 07 — shared standards

What applies across all three programmes

Data and privacy

Learner data is not shared with third parties for advertising. Session recordings and submitted work are kept within the school's own systems.

Content updated each cohort

Library versions, framework changes and shifts in standard practice are checked before each new cohort begins — not just when someone raises an issue.

Feedback reviewed before delivery

Written feedback on submissions is checked by the Programme Director before being sent. A templated response is not acceptable and would be flagged.

All sessions recorded

Recordings are available the same evening. Missing a session due to work or family commitments should not mean falling permanently behind.

Open help channel

Learners can post questions at any time. Instructors respond within one working day, not only at the next live session.

Week 1 material readable before enrolment

Each programme makes its first week's content available to read at no cost so you can judge the format, density and pace before making any commitment.

# cell 08 — fees

Programme fees in Malaysian Ringgit

programme 01

Python for AI Work

RM 125

One-time fee · 4 weeks

4 weeks of material
Weekly office hours
Open help channel
Withdraw in first 2 weeks

Enquire

programme 02

Deep Learning Foundations

RM 370

One-time fee · 10 weeks

10 weeks of material
Mentor training run reviews
Written feedback on submissions
One free module repeat

Enquire

programme 03 · most popular

Applied Machine Learning

RM 650

One-time fee · 16 weeks

16 weeks of material
2 live evening sessions/week
4 projects with written feedback
End-to-end deployment project

Enquire

# cell 09 — not sure where to start

Tell us your background and we will suggest the right module

We respond to all enquiries with a straight recommendation, not a sales pitch. Use the form to send a brief description of what you already know.

Get in Touch