The curriculum
Three courses, one clear path through AI
Each programme is self-contained and practical. Together, they take you from the basics of machine learning all the way to running models in production.
Back to HomeHow we teach
Our teaching methodology
Each Khwamru course is built around the same core structure: short lessons that introduce one idea at a time, followed by an exercise that lets you apply it straight away. We don't move on until the current concept is clear, and we write in plain English throughout.
Read
Short, clear lessons introduce each concept. We keep explanations focused and avoid unnecessary detours.
Practice
Exercises follow each lesson. You run real code in a working environment, not a sandboxed simulation.
Build
At the end of each section, a small project brings the pieces together. These accumulate into a meaningful portfolio over the course.
Course 01
Foundations of Machine Learning
A patient, thorough introduction to the core ideas of machine learning, with guided practice throughout. A comfortable starting point for anyone new to the field who wants to understand how these methods work and when to use them.
What you'll work through:
- Supervised learning — regression and classification
- Unsupervised learning — clustering and dimensionality reduction
- Model evaluation and cross-validation
- Feature engineering and data preparation
- Working with scikit-learn and standard Python libraries
How the course is structured:
Introduction to data and prediction problems — what machine learning is, and where it helps
Linear models — building intuition before complexity
Tree-based methods and ensemble learning
Evaluation, tuning, and final project
Course fee
฿1,950 THB
Course 02
Applied Deep Learning
A hands-on programme building neural networks through small, achievable projects and clear explanations. Designed for learners who want to grow their skills gradually and with support. The course assumes some familiarity with Python and basic ML concepts.
What you'll work through:
- Neural network fundamentals — layers, activations, backpropagation
- Convolutional networks for image tasks
- Recurrent architectures and sequence data
- Transfer learning from pre-trained models
- Training, debugging, and improving models with PyTorch
How the course is structured:
How neural networks learn — a visual and mathematical walkthrough
Image classification project with CNNs
Sequence modelling and natural language basics
Capstone project — build and evaluate a model of your choosing
Course fee
฿5,750 THB
Course 03
Model Deployment & MLOps
A calm, practical guide to taking models into everyday use, from packaging to monitoring. Helpful for those who would like their projects to run dependably in the wider world — or for engineers who need to support ML models within a software team.
What you'll work through:
- Packaging ML models for production
- REST API serving with FastAPI
- Containerisation with Docker
- Monitoring model performance over time
- CI/CD basics for ML pipelines
How the course is structured:
From notebook to service — what changes when a model goes live
Building and deploying a prediction API
Infrastructure, scaling, and keeping things running
Monitoring, logging, and handling model drift
Course fee
฿3,700 THB
Choose your starting point
Which course is right for you?
The three courses can be taken in sequence, or you can join at the level that matches your current skills.
| Feature | Foundations of ML | Applied Deep Learning | Model Deployment |
|---|---|---|---|
| Prior knowledge needed | Basic Python | Python + ML basics | Python + some ML/DL |
| Typical duration | 4–6 weeks | 7–10 weeks | 5–7 weeks |
| Price (THB) | ฿1,950 | ฿5,750 | ฿3,700 |
| Hands-on projects | |||
| Neural network content | — | Some | |
| Best for | New to AI, building foundations | Ready for deep learning | Getting models into production |
How we operate
Standards across all courses
Data privacy
Your personal information and course progress are not shared with third parties. We handle data in accordance with applicable Thai data protection law.
Regular content review
Courses are reviewed every six months. When tools or libraries change in ways that affect the curriculum, updates are made and enrolled learners are notified.
Responsive instructor support
We respond to learner questions within one working day. Support is provided by the instructors who wrote the content, not a separate team.
Tested code throughout
All code in course materials is verified to run on current library versions before publication. Setup guides are included so you're not left troubleshooting your environment.
Permanent access
Enrolment does not expire. If you need to take a break and return to the material later, you'll find it waiting — along with any updates made since you last visited.
Payment documentation
We provide receipts and course descriptions suitable for professional development expense claims. Ask us when you enquire and we'll prepare the documentation you need.
Investment
Course pricing
Each course is a single, complete purchase. No subscriptions. No separate fees for exercises or support.
Course 01
Foundations of Machine Learning
฿1,950
Thai Baht · one-time
- All course lessons
- Exercises and datasets
- Instructor support
- Permanent access
Course 02
Applied Deep Learning
฿5,750
Thai Baht · one-time
- All course lessons
- Four hands-on projects
- Instructor support
- Permanent access
- PyTorch environment setup guide
Course 03
Model Deployment & MLOps
฿3,700
Thai Baht · one-time
- All course lessons
- Deployment projects
- Instructor support
- Permanent access
Not sure where to start?
Tell us about your background and what you're hoping to do with AI. We'll suggest which course to begin with and explain what to expect before you commit to anything.
Send an Enquiry