— Our Courses
Three courses. One clear direction: understanding that holds up.
From a first look at machine learning to an extended mentorship programme — each path is built around project work, honest feedback, and a realistic time commitment.
Back to Home— Our Methodology
How every course is built
Each Panya AI course follows the same structure: concepts are introduced with clear explanations, applied through a project that uses real tools, and reviewed by a mentor who gives specific written feedback. That cycle repeats across the duration of the course, building progressively on what came before.
We don't use time-pressure mechanics or peer leaderboards. Progress is measured against the quality of the work, not against other learners. If a topic takes longer to absorb, we'd rather you absorb it properly.
Structured lessons
Clear sequencing, no assumed knowledge beyond stated prerequisites
Real project work
Using actual ML libraries in notebook and script environments
Written mentor feedback
Specific to your work, within 5 working days
Iterative progression
Each course module builds on the understanding from the last
Foundations of Machine Learning
A patient introduction to the core ideas behind machine learning, from data and features to training and evaluation. This course is suited to learners with basic programming familiarity who want a solid, honest grounding. It spans around eight weeks of part-time study and includes guided lessons, small hands-on projects, and mentor feedback.
What's covered
- Data loading, cleaning, and feature engineering in Python
- Supervised learning: regression and classification
- Model evaluation, overfitting, and cross-validation
- Scikit-learn workflows and model selection
- Capstone project with mentor review
How the course runs
Work through structured lessons at your own pace, typically 8–10 hours per week
Complete small projects after each module and submit them for mentor review
Receive written feedback within 5 working days and revise your work if needed
Complete a capstone project to receive your certificate of completion
Course fee
฿4,500
Applied Deep Learning
A practical course building neural networks for real tasks, with careful attention to understanding rather than shortcuts. Suited to those comfortable with Python and the basics of machine learning. Spans around ten weeks part-time. Includes project work, code reviews, and supportive mentor guidance.
What's covered
- Neural network fundamentals and backpropagation
- Convolutional networks for image tasks
- Recurrent architectures and sequence modelling
- Transfer learning with pre-trained models
- Full project with code review and mentor feedback
How the course runs
Prerequisites check — your mentor confirms your Python and ML readiness before you begin
Work through modular lessons, each followed by a practical exercise in PyTorch
Submit code for review — mentor assesses both correctness and engineering choices
Build and present a final project applying deep learning to a chosen real-world problem
Course fee
฿11,200
AI Development Mentorship Track
An extended, mentor-led track for learners building toward a portfolio of applied AI work. We support steady progress through structured projects and regular feedback, at a pace that respects each learner's commitments. Spans around four months part-time. Includes one-to-one mentoring, project guidance, and a portfolio review.
What's covered
- Three substantial applied AI projects across different domains
- Regular one-to-one sessions with your assigned mentor
- Current tools: HuggingFace transformers, LangChain, deployment basics
- Portfolio review and written mentor assessment at completion
- Flexible pacing — adjusted to your schedule with mentor support
How the track runs
Intake call with your mentor to assess where you are and agree on a realistic schedule
Work through a guided project sequence, meeting with your mentor every two weeks
Submit work between sessions for written feedback; adjust direction based on responses
Final portfolio review session — discuss the work, what you'd do differently, what comes next
Track fee
฿17,400
— Choose Your Path
Which course is right for you?
Not sure where to start? Use this table or send us a message — we'll respond with a clear recommendation.
| Feature | Foundations | Deep Learning | Mentorship Track |
|---|---|---|---|
| Duration | 8 weeks | 10 weeks | 4 months |
| Python prerequisite | Basic | Intermediate | Intermediate+ |
| Written project feedback | |||
| One-to-one mentor sessions | |||
| Portfolio review session | |||
| Certificate of completion | |||
| Best for… | First steps in ML | Building neural networks | Portfolio-level AI work |
| Fee | ฿4,500 | ฿11,200 | ฿17,400 |
— Standards Across All Courses
What every learner can expect
Data privacy
Learner data is not shared with third parties. We handle it carefully and according to our published privacy policy.
5-day feedback commitment
All project submissions receive written feedback within 5 working days. If there's a delay, you'll be notified in advance.
Curriculum updated biannually
Course materials are reviewed every six months to reflect changes in tools and practices in the field.
Clear enrolment terms
Everything that's included in the course fee is stated before you pay. No hidden costs discovered later.
Async support channel
Every enrolled learner has access to an async messaging channel with their mentor for questions between submissions.
Flexible pace accommodated
If your schedule changes, let your mentor know. Timeline extensions are handled case by case without automatic penalties.
— Pricing
All-inclusive fees, no add-ons
Foundations
8 weeks · Part-time
฿4,500
one-time fee
- Full lesson access
- Module project reviews
- Capstone project feedback
- Certificate of completion
Applied Deep Learning
10 weeks · Part-time
฿11,200
one-time fee
- Full lesson access
- Code reviews on all exercises
- Final project feedback
- Certificate of completion
Mentorship Track
4 months · Part-time
฿17,400
one-time fee
- Three applied AI projects
- Bi-weekly one-to-one sessions
- Full written feedback on all work
- Portfolio review and assessment
- Certificate of completion
Still deciding? Ask us directly.
Send a message through our contact form and a mentor will come back to you with an honest recommendation — usually within one working day.
Get in Touch