Three Courses, One Clear Path
Whether you're writing your first Python script or you're ready to build a complete AI project with a mentor, Syntharidas has a track that fits where you are.
Back to HomeHow Our Courses Are Structured
Every Syntharidas course follows the same basic pattern: a topic is introduced briefly, you read or watch a short explanation, then you apply it to a small project. After submitting your work, you receive written feedback before moving to the next topic.
This loop — introduce, apply, review — is repeated throughout the course. It takes more instructor time than a video-only format, but it's what makes the material stick rather than fade after the course ends.
The three tracks are designed to connect. Foundations builds the base. Applied ML Engineering extends it into production patterns. The Capstone applies everything to a real problem chosen by the learner.
Typical Learning Cycle
Topic introduction with worked example
Hands-on exercise using a real dataset
Submit work for instructor review
Receive written feedback (within 3 days)
Review notes and move to next topic
Foundations of AI Development
A beginner-friendly course covering Python fundamentals, data handling, and core machine-learning ideas through small, guided projects. Suited to newcomers with little prior coding. Runs over roughly twelve weeks part-time, with weekly exercises and feedback. Includes a course completion record.
- Python syntax and data structures
- Working with tabular data using pandas
- Introduction to scikit-learn models
- Weekly feedback on submitted exercises
- Completion record on finishing
Applied Machine Learning Engineering
An intermediate course on building, evaluating, and packaging models, with an introduction to workflow tooling and deployment basics. For learners comfortable with Python who want practical, project-based experience. Includes code reviews and a portfolio project.
- Model evaluation and validation patterns
- Experiment tracking and reproducibility
- Model packaging and deployment basics
- Code reviews on all major submissions
- Portfolio project on completion
Mentored Capstone Track
A guided track pairing learners with a mentor to plan and complete an applied AI project from idea to working prototype. Designed for those ready to consolidate their skills into a portfolio piece. Includes regular one-to-one sessions and a community cohort.
- Domain-matched mentor assignment
- Regular one-to-one video sessions
- Project scoping and planning support
- Working prototype deliverable
- Community cohort access throughout
Which Track Is Right for You?
A side-by-side view of what each course includes.
| Feature | Foundations | Applied ML Eng. | Capstone |
|---|---|---|---|
| Python basics | assumed | assumed | |
| Data handling (pandas) | assumed | ||
| Model building & evaluation | intro | ||
| Deployment basics | |||
| Code reviews | |||
| One-to-one mentor sessions | |||
| Portfolio project | |||
| Price | ฿3,900 | ฿18,000 | ฿34,000 |
best for
Foundations
New to coding or Python. Curious about AI but unsure where to start.
most popular
Applied ML Engineering
Comfortable with Python and want practical ML skills for real projects.
best for
Capstone Track
Have ML experience and want to build a complete project with expert guidance.
What Applies Across All Tracks
Privacy & Data Security
Learner data handled in line with Thailand's PDPA. We keep only what's needed to deliver the course.
Regular Content Updates
Course material reviewed every six months. When tools or practices change meaningfully, the content follows.
Feedback Turnaround
Submitted exercises reviewed within three working days. Code reviews in the Applied track within two.
Learner Support Channel
Questions about course content reach an instructor, not a support bot. Response within one business day.
Small Cohort Sizes
We limit cohort intake so instructors can give each learner's work proper attention. No mass-enrolment drops.
Transparent Scope
Each course page states clearly what's covered, what background is needed, and what you'll have when you finish.
Course Fees
All prices in Thai Baht. Applicable VAT stated at checkout. No hidden add-ons.
Foundations
฿3,900
one-time enrolment fee
- ~12 weeks part-time
- Weekly exercise feedback
- Completion record
- Cohort community access
Applied ML Engineering
฿18,000
one-time enrolment fee
- Project-based curriculum
- Code reviews on submissions
- Portfolio project
- Deployment basics included
Mentored Capstone
฿34,000
one-time enrolment fee
- Domain-matched mentor
- Regular one-to-one sessions
- Working prototype output
- Community cohort
Not Sure Where to Start?
Send us a short message about your background and what you want to learn. We'll suggest the most sensible starting point.
Get in Touch