Course Tracks

Three Tracks, One Clear Direction

From a first Python script to an advanced capstone project — Neuronest's three tracks cover the full path of AI development with mentor support at every stage.

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Methodology

How the Neuronest Curriculum Works

Each track is structured as a series of layered exercises. A concept is introduced, then applied immediately in a small, guided task before the next concept builds on top of it. This sequencing means understanding accumulates rather than sitting in isolation.

All tracks include project submissions with written mentor feedback. The process from problem framing to a working result is the same whether a learner is handling a small notebook exercise or a full capstone project.

Tracks can be completed individually or in sequence. Learners who complete Foundations have the preparation needed for Applied ML, and Applied ML graduates are well positioned for the Advanced track.

Top-Down Sequencing

Each concept prepares the ground for the next. No topic appears out of order.

Practice Before Progress

Exercises follow each concept immediately so understanding is tested before moving on.

Mentor Review

Submitted projects receive written notes from an experienced reviewer, not automated scoring.

Portfolio Output

Every track produces documented artefacts a learner can point to and share.

Track 01 Beginner

Foundations of AI Development

A beginner-friendly track covering Python for data work, core mathematics for machine learning, and how models learn from data. Built around small, guided exercises so concepts settle through practice. Suited to newcomers with steady commitment; learners finish with a portfolio of starter notebooks.

Python for data science from scratch
Core mathematics introduced alongside code
How models learn from data, explained clearly
Portfolio of documented starter notebooks

How You Progress

Set up your Python environment and learn data structures

Explore and transform datasets with pandas

Introduce core ML mathematics and build your first model

Document and submit your starter portfolio notebooks

฿3,400 Enquire

Track 02 Intermediate

Applied Machine Learning

An intermediate track on building, evaluating, and improving models with real datasets, including good data habits and honest measurement. Covers project workflows from problem framing to a working result. Learners build several end-to-end projects with mentor feedback.

Full project workflow: framing to working result
Honest measurement and model evaluation
Real, messy datasets — not toy benchmarks
Mentor-reviewed end-to-end project submissions

How You Progress

Frame a problem and gather appropriate data

Clean, explore, and prepare the dataset

Select, train, and evaluate multiple model approaches

Iterate based on mentor feedback and document findings

฿7,500 Enquire

Track 03 Advanced

Advanced Systems & Capstone

A senior track on modern model architectures, responsible deployment, and a substantial capstone project of the learner's choosing. Emphasises sound engineering and clear documentation. Includes regular reviews and a presented final project to add to a portfolio.

Modern model architectures and deployment practices
Responsible AI engineering integrated throughout
Learner-chosen capstone for genuine ownership
Regular reviews and a presented final project

How You Progress

Study modern architectures and deployment considerations

Define your capstone project scope with mentor input

Build, document, and present regular milestone reviews

Present and document the final project for your portfolio

฿11,900 Enquire

Choose Your Path

Which Track Is Right for You?

Feature	Foundations	Applied ML	Advanced
Prior experience needed	None	Foundations level	Applied ML level
Mentor feedback
Real dataset exercises
End-to-end project workflow	—
Learner-chosen capstone	—	—
Deployment and architecture	—	—
Price (฿)	3,400	7,500	11,900

Not sure where to start?

If you have no prior coding experience, start with Foundations. If you are comfortable with Python and basic data manipulation but have not built and evaluated ML models yet, Applied ML is the right entry point. Get in touch and we can help you assess which level fits best.

Standards

Shared Across All Tracks

Open-Source Tooling

All exercises use Python and the standard open-source data science and ML ecosystem. No proprietary tools or locked-in platforms.

Documentation Standards

Every submission is expected to include clear documentation. This expectation is set from the first Foundations exercise and applied consistently through Advanced.

Data Privacy Compliance

Learner data is handled in line with Thailand's PDPA. Data collected during enrolment is used for education delivery only.

Six-Monthly Content Review

All three tracks are reviewed every six months. Outdated exercises are rewritten to stay aligned with current tooling and practices.

One-Day Support Response

Support enquiries from enrolled learners are answered within one working day. Support covers both technical and conceptual questions.

Responsible AI Integration

Bias awareness, fairness considerations, and honest evaluation practices are threaded through all tracks from the first exercise.

Pricing

Simple, One-Time Track Pricing

Pay once per track. No subscriptions or hidden fees.

Track 01

Foundations

฿3,400

one-time

Python for data work
Core ML mathematics
Guided exercises
Starter notebook portfolio
Email support

Enquire

Applied ML

฿7,500

one-time

End-to-end project workflow
Real datasets
Honest model evaluation
Mentor-reviewed projects
Email support

Enquire

Track 03

Advanced

฿11,900

one-time

Modern architectures
Responsible deployment
Learner-chosen capstone
Regular milestone reviews
Priority support

Enquire

Ready to Choose a Track?

Send an enquiry and we will confirm the right starting point, share onboarding details, and answer any questions before you commit.

Enquire Now