Three tracks.
One clear progression.
Each Cogwright course is built around practical projects. Here you will find what each track covers, how it runs and what you will have when you complete it.
← Back to HomeOur teaching methodology
Project briefs, not abstract exercises
Every learning unit begins with a project brief — a defined thing you will build. This keeps the work concrete and gives you something to show at the end.
Feedback on your actual submissions
Instructors review what you write. Written feedback addresses your specific code, not a model answer. This is how meaningful learning happens in development work.
Tracks that build on each other
The three tracks form a deliberate progression. Completing Basics gives you the foundation for Workshop Track. Workshop Track feeds into Applied AI Engineering without significant gaps.
Programming & AI Basics
฿3,900 · 8 weeks
A starting course for people who have not written code before. You will learn Python and encounter the foundational ideas of artificial intelligence by working through a series of small, buildable projects. Lessons are recorded and available to watch at any time. Written guides accompany each lesson so you can read, search and refer back without rewatching video.
Mentor feedback is included throughout — when you submit a project, an instructor reviews it and provides written notes on what works and what could be approached differently. You also join a learner community running alongside the course, where other students at the same stage are working through the same material.
What you will cover:
- Python syntax, data structures and control flow
- Functions, modules and working with files
- Introduction to AI concepts — what models are and how they learn
- Small project: building a simple classification or prediction tool
- Completion record provided for your portfolio
How the 8 weeks are structured:
- 01Setting up your environment and Python first steps
- 02Data structures and writing useful functions
- 03Reading, writing and handling data from files
- 04What AI models are — a practical introduction
- 05Working with a simple dataset
- 06Building and running a small model
- 07Testing and improving your project
- 08Final submission and feedback
Best for
People with no coding background who want to understand what Python is and how AI systems work, through hands-on building rather than watching lectures.
Best for
Learners who can already write basic Python and want to build real machine learning projects using tools that practitioners use, with code review on their work.
Machine Learning Workshop Track
฿15,800 · 12 weeks
An intermediate track for learners with some Python experience. You will build practical ML projects using popular open-source libraries — creating models, testing them and understanding why they behave as they do. Code review is central to the track: you submit project work and receive detailed written feedback from an instructor.
The track includes group discussion sessions where learners share approaches and compare results. You will also complete a portfolio project that you review and refine based on feedback — something you can reference when discussing your practical ML work.
What you will cover:
- Core ML concepts: supervised learning, model evaluation, overfitting
- Working with popular Python ML libraries
- Data preparation and feature engineering
- Building, training and evaluating models
- Portfolio project with instructor code review
How the 12 weeks are structured:
- 01–02Environment setup and data preparation techniques
- 03–04Supervised learning — classification and regression projects
- 05–06Model evaluation and performance improvement
- 07–09Portfolio project development with interim review
- 10–11Refinement based on feedback and peer discussion
- 12Final project submission
Applied AI Engineering
฿32,500 · 16 weeks
An advanced programme for experienced programmers who want to work on the full AI application cycle. You will design, train and deploy AI systems — covering data pipelines, model evaluation, and integration with real environments. The programme ends with a capstone project developed with mentor guidance and peer support.
This track goes beyond modelling. It addresses the engineering decisions made when putting AI systems into use: how to structure data pipelines, how to evaluate models for real use cases, and how to integrate trained systems into applications. These are the parts of AI development that are often under-taught in introductory material.
What you will cover:
- Data pipeline design and management
- Advanced model training and evaluation approaches
- AI system deployment and real-world integration
- Monitoring, maintenance and iteration of deployed systems
- Mentored capstone project from brief to deployed application
How the 16 weeks are structured:
- 01–03Data engineering foundations and pipeline construction
- 04–06Advanced model design and evaluation methodology
- 07–09Deployment patterns and system integration
- 10–12Capstone project development with mentor check-ins
- 13–15System testing, iteration and peer review
- 16Final capstone submission
Best for
Experienced programmers who understand ML basics and want to learn the engineering side — building and deploying complete AI systems with a mentor-guided capstone project.
Which course fits where you are?
Use this comparison to decide which track matches your current level and goals.
| Feature | Basics ฿3,900 |
ML Workshop ฿15,800 |
Applied AI ฿32,500 |
|---|---|---|---|
| Duration | 8 weeks | 12 weeks | 16 weeks |
| Required background | None | Basic Python | Experienced programmer |
| Recorded lessons | |||
| Written guides | |||
| Mentor feedback on submissions | |||
| Learner community access | |||
| Code review on project work | |||
| Portfolio project | |||
| Mentored capstone project | |||
| Deployment and integration coverage |
Standards shared across every Cogwright course
Data privacy
Learner data is used only for course administration. Nothing is shared with third parties for marketing.
Content kept current
Material is reviewed when libraries or standard practices change significantly. Active learners are notified of updates.
Feedback within a defined window
Submitted work receives mentor feedback within a clear turnaround time. Enquiries receive a response within one business day.
Written content alongside all video
Every recorded lesson comes with a written guide. You can study in the format that works better for you and search or reference material without rewatching.
Community throughout the course
Access to the learner community is included for the full course duration. The channel gives you a place to think through problems alongside peers at the same stage.
All-inclusive pricing
The listed price covers everything in the course description. There are no add-on charges for materials, feedback or community access.
Course fees
All prices in Thai Baht. Each fee is all-inclusive — no add-ons.
Track 01
Basics
฿3,900
8-week course
- All lessons and written guides
- Mentor feedback on submissions
- Learner community access
- Completion record
Track 02
ML Workshop
฿15,800
12-week track
- All lessons and written guides
- Mentor feedback and code review
- Learner community access
- Portfolio ML project
Track 03
Applied AI
฿32,500
16-week programme
- All lessons and written guides
- Mentor feedback and code review
- Learner community access
- Mentored capstone project
Not sure which track to start with?
Send us a message about your background and what you are hoping to learn. We will point you toward the track that makes the most sense and answer any questions about the material or format.
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