Three programmes, one clear progression
Each course has its own scope and sits naturally in sequence with the others. You can join at the level that fits where you are now and move forward from there.
Back to HomeOur teaching methodology
Each programme at Witaya Lab follows the same underlying structure: a clear statement of what it covers and what it assumes, a sequence of exercises that build on each other, written feedback from a mentor, and regular one-to-one sessions to check understanding and answer questions.
We do not teach to a test. The exercises produce things that work — code that runs, models that classify, projects that function. The goal is to leave each course with skills you can actually use.
Clear prerequisites
Know what you need before you start
Practical exercises
Each session produces something that runs
Mentor feedback
A person reads your work and responds
Real output
A portfolio of work, not just a certificate
Python for AI Beginners
A gentle, well-paced entry point into programming for data and AI. This course covers Python fundamentals — variables, data structures, functions, file handling — with exercises that connect each concept to work you would actually do with data. By the end, learners can write readable, working Python scripts and are ready to move into machine learning topics with confidence.
Prerequisites, clearly stated:
No prior programming experience needed. Comfort using a computer for everyday tasks (browsing, files, email) is enough to begin. If you have used spreadsheets for data work, you are well placed to start here.
What you will work on:
- Python syntax, data types, and control flow
- Working with lists, dictionaries, and data files
- Introduction to Pandas for tabular data
- Writing functions and structuring readable scripts
- A small end-of-course data exploration project
How the course runs:
Each week covers a new topic with a reading section and a coding exercise.
You submit your exercise and receive written feedback from your mentor within two working days.
A one-to-one session at weeks three and six reviews your progress and answers accumulated questions.
The final week involves a small independent project, reviewed and discussed with your mentor.
Natural Language Processing
A practical course in how machines understand and generate language. Covering text cleaning and tokenisation, classical NLP methods, and modern transformer-based models, this programme builds from first principles toward the kind of language model work that appears in current AI applications. Explanation is careful throughout — the goal is understanding, not just running pre-written code.
Prerequisites, clearly stated:
Comfortable Python programming is needed — the level reached by completing the Python for AI Beginners course, or equivalent. Familiarity with basic machine learning concepts (what a model is, what training means) is also needed. If you are uncertain whether you qualify, contact us and we will talk it through.
What you will work on:
- Text preprocessing: cleaning, tokenisation, and normalisation
- Text classification and sentiment analysis projects
- Word embeddings and sequence models
- Transformer architecture and working with pre-trained models
- A hands-on NLP application project
How the course runs:
Weekly topics build progressively — each week assumes you have absorbed and practised the previous one.
Exercises are submitted for mentor review. Feedback arrives within two working days.
One-to-one sessions at weeks three, six, and nine track progress and work through difficult concepts.
The final two weeks involve a structured NLP project chosen with your mentor's input.
Applied AI Project Track
A mentor-led track where learners define, plan, and build a substantial AI project from beginning to working result. The scope is yours — a recommendation system, a classification tool, a text generation application, or something else entirely — provided it involves applying machine learning or NLP to a real problem. Progress is reviewed regularly, and the track concludes with a structured final assessment.
Prerequisites, clearly stated:
Solid Python skills and experience with at least one area of machine learning or NLP are needed before joining this track. Completing both the Python for AI Beginners and NLP courses provides full preparation. Learners with equivalent independent study may also qualify — contact us to discuss.
What you will work on:
- Scoping a real AI project with clear requirements
- Data collection, preparation, and exploratory analysis
- Model selection, training, and iteration
- Evaluation, documentation, and deployment basics
- Final project assessment and structured review
How the track runs:
Week one: project scoping session with your mentor to define the problem and plan the work.
Biweekly review sessions throughout. You submit progress updates; your mentor reads and responds.
Mid-track checkpoint at six weeks reviews what you have built and adjusts the plan if needed.
Final assessment: a working project, documentation, and a one-hour discussion with your mentor.
Which course is right for you?
Use this to compare what each course covers and what it assumes.
| Feature | Python Beginners | NLP Course | Project Track |
|---|---|---|---|
| Prior programming needed | None | Python | Python + ML |
| Duration (part-time) | ~6 weeks | ~9 weeks | ~3 months |
| Own project work | Guided exercises | Small project | Full project |
| Mentor sessions | 2 sessions | 3 sessions | Biweekly |
| Final assessment | Project review | Project review | Formal assessment |
| Price (Thai Baht) | ฿4,200 | ฿10,800 | ฿16,900 |
Best for: complete beginners
→ Start with Python for AI Beginners
Best for: those comfortable with Python
→ Move into Natural Language Processing
Best for: ready to build something
→ Join the Applied AI Project Track
How all three courses operate
Shared commitments that apply across every programme.
Data privacy
Learner data — work submissions, contact details, session notes — is stored securely and handled under Thailand's PDPA requirements.
Regular content review
Course materials are reviewed every six months. Library versions and coding standards are updated to stay aligned with current practice.
Feedback turnaround
Mentors commit to two working days for exercise feedback. If a review takes longer, the learner is notified promptly.
Accessible delivery
Materials load on standard connections and are designed to work on any device with a modern browser — no specialist software required.
Honest scope
No course promises specific employment or salary outcomes. We describe what you will learn and what you will be able to do — and keep those descriptions accurate.
Admin support
Questions about enrolment, scheduling, or payments are handled within one working day. Office hours run Monday to Friday, 9:00–18:00.
Clear, fixed prices in Thai Baht
One payment per course. Mentor support, materials, and one-to-one sessions all included.
Python for AI Beginners
฿4,200
One-time payment · ~6 weeks
- All course materials
- Exercise feedback × 6 weeks
- 2 one-to-one mentor sessions
- Final project review
Natural Language Processing
฿10,800
One-time payment · ~9 weeks
- All course materials
- Exercise feedback × 9 weeks
- 3 one-to-one mentor sessions
- NLP project review
Applied AI Project Track
฿16,900
One-time payment · ~3 months
- Project scoping support
- Biweekly mentor reviews
- Progress submissions + feedback
- Final assessment session
Not sure which course to start with?
Tell us a little about where you are now and what you are hoping to learn. We will suggest the course that makes sense — no pressure.
Ask Us