Three Courses.
One Connected Path.
Each Loomlogic course is designed to be taken in sequence — but you can join at any level that matches your background. Here's what each one covers.
Back to HomeHow the Curriculum Is Built
Concept with Context
Every topic is introduced with a working example. You see it before you're asked to understand it abstractly.
Guided Task
Each concept is followed by a structured task. You apply what you just read using real tools on real data.
Reflection and Review
After each module, a short review consolidates what was built and points forward to where it leads in the next stage.
Output for Portfolio
The course closes with a documented output — code, a trained model, or a project write-up — that you can keep and show.
AI Development Starter Course
A foundational course that introduces programming basics, data literacy, and the core concepts behind AI — all through small, complete projects. By the end, you'll have written working Python code, read and organised a real dataset, and built a simple predictive model from scratch.
What You'll Cover
- Python fundamentals: variables, functions, loops, and libraries
- Reading, inspecting, and cleaning tabular data with pandas
- Visualising data patterns with matplotlib
- Core ML concepts: training, testing, and evaluating a model
- Setting up a reproducible project environment with Git
Process
Set up your development environment and write your first Python script
Work through three guided data tasks of increasing complexity
Build and evaluate a simple classification model on a provided dataset
Document your work in a GitHub repository as your first portfolio entry
Data & Models Practicum
An intermediate course built around guided practical tasks. You'll work through the full cycle of data preparation, model building, and evaluation — the core of most professional AI work. Each task is more open-ended than the Starter Course, requiring you to make decisions and justify your approach.
What You'll Cover
- Advanced data cleaning: handling missing values, outliers, encoding
- Feature engineering and selection techniques
- Supervised learning: regression and classification with scikit-learn
- Unsupervised learning: clustering and dimensionality reduction
- Model evaluation: cross-validation, metrics, and iteration
- Documenting and presenting model choices and results
Process
Receive a raw dataset; conduct exploratory analysis and produce a data report
Clean and engineer features; justify your decisions in a short write-up
Train multiple model types; evaluate and compare their performance
Document your full pipeline as a reproducible notebook
Capstone Mentorship Track
A mentored track built around a substantial project that you define. You work with a Loomlogic mentor through scheduled feedback sessions and portfolio-focused review. The output is a complete, documented project that represents what you can do as an AI developer — suitable for presenting to anyone who asks.
What's Included
- Project scoping session with your assigned mentor
- Scheduled feedback sessions at key project milestones
- Review of data strategy, model selection, and pipeline design
- Portfolio write-up guidance: structure, language, technical depth
- Presentation practice: explaining your work to a non-technical audience
Track Phases
Define project scope, objectives, and success criteria with mentor
Build and iterate on your project with structured mentor check-ins
Write up your project: context, approach, results, and limitations
Present your work in a final review session with mentor feedback
Which Course Is Right for You?
Compare what's included in each level to find your entry point.
| Feature | Starter ฿3,900 |
Practicum ฿17,000 |
Capstone ฿32,800 |
|---|---|---|---|
| No prior coding required | |||
| Python and data tools covered from scratch | |||
| Model building and evaluation tasks | |||
| Advanced data preparation workflows | |||
| Self-defined project | |||
| 1-on-1 mentor feedback sessions | |||
| Portfolio write-up and presentation review |
Best for →
Anyone new to programming who wants a solid start in AI development
Best for →
Learners with basic Python who want to go deep on data work and modelling
Best for →
People with solid skills who want a real project and structured mentorship to complete it
Across All Three Courses
Data Privacy
All datasets used in course tasks are either public-domain or synthetic. No real personal data is used in any exercise.
Regular Content Updates
Course materials are reviewed and revised every six months. Enrolled learners get access to updated versions at no extra cost.
Responsive Support
Email questions are answered within one working day. We don't route learners through automated helpdesks.
No Special Hardware Needed
All course tasks can be run in cloud-based notebook environments. A standard laptop and a browser are sufficient for every module.
Open-Source Tooling Only
Every tool used in Loomlogic courses — Python, pandas, scikit-learn, Git — is open-source and freely available. No paid software required.
Personal Data Handled Under PDPA
Learner information is stored and processed in line with Thailand's Personal Data Protection Act. Details in our Privacy Policy.
Course Fees
฿3,900
One-time enrolment
- Full course access
- All guided tasks and datasets
- Email support
- Content updates included
฿17,000
One-time enrolment
- Full course access
- All guided tasks and real datasets
- Email support
- Content updates included
- Instalment option available
฿32,800
Includes mentorship sessions
- Full track access
- 1-on-1 mentor feedback sessions
- Portfolio write-up review
- Final presentation session
- Instalment option available
Not Sure Which Level Fits?
Drop us a message and describe where you are. We'll give you an honest assessment of the right entry point.
Get in Touch