Our Courses
Three Courses, One Thoughtful Path into AI
Each Samong course is self-contained and also builds toward the next. Begin wherever fits your current knowledge, and go as far as you want to go.
← Back to HomeHow Samong Courses Work
A Learning Experience Built Around You
Every course at Samong follows the same underlying approach: lessons are structured to build understanding step by step, exercises reinforce each idea before you move on, and a mentor is available to give feedback on what you submit. There is a project at the heart of each course — something you plan, build, and refine over the course period.
Unlike many online courses that drop you into a long video library and leave you to find your own way, Samong courses have a clear weekly rhythm. You know what you are doing each week and why it matters for where you are going.
The pace is calibrated to be manageable alongside other commitments — most learners spend six to ten hours per week. If something comes up and you need to slow down for a period, you can do that without falling behind permanently.
Structured Weekly Flow
Clear milestones each week so you always know what comes next.
Exercise-First Learning
You practise each concept before moving on, not just read about it.
Mentor-Reviewed Work
A real person reads and responds to what you submit.
Portfolio as the Goal
Every course produces a project that belongs to you after it ends.
AI Basics for Beginners
A warm introductory course for those new to AI development. We introduce the core ideas gently, show the tools in a friendly, step-by-step way, and offer small hands-on tasks so learning feels natural. Suited to curious newcomers and career changers taking a first step. Includes structured lessons, practice notebooks, and mentor feedback, at a comfortable pace over roughly eight weeks.
What you will work through:
- Introduction to AI concepts — what it is, what it is not, and where it applies
- Python fundamentals needed for AI work
- Working with data: loading, cleaning, and understanding datasets
- A first look at simple models and how they learn
- A small introductory project reviewed by your mentor
How it is structured:
Weeks 1–2: Core AI concepts and Python setup
Weeks 3–4: Data fundamentals and your first notebooks
Weeks 5–6: Simple models — training and evaluating
Weeks 7–8: Introductory project and mentor review
Practical Machine Learning
A hands-on course for learners ready to build models and understand how they work. We move through data preparation, training, and evaluation with real, guided tasks, supporting you as you develop a small portfolio project. Well suited to those with the basics who would like deeper practice. Includes mentor reviews, discussion sessions, and a scope of around ten to twelve weeks.
What you will work through:
- Data preparation in depth — pipelines, feature engineering, validation
- Supervised learning: classification and regression with real datasets
- Model evaluation — metrics, overfitting, and model selection
- Introduction to neural networks and how they differ
- Portfolio project developed with mentor guidance and code review
How it is structured:
Weeks 1–3: Data preparation and feature engineering
Weeks 4–6: Supervised learning with guided tasks
Weeks 7–9: Evaluation, tuning, and neural networks intro
Weeks 10–12: Portfolio project — build, refine, and present
Full AI Development Track
A comprehensive, mentor-supported track for learners aiming to build and deploy complete AI systems. It spans model development, serving, monitoring, and responsible practice, centred on a substantial portfolio project you shape with guidance. Recommended for committed learners preparing for professional work. Includes regular one-to-one mentorship, code review, and a considered schedule across several months.
What you will work through:
- Advanced model development: deep learning and modern architectures
- Model serving and API development for AI applications
- Monitoring models in production — drift, performance, and alerting
- Responsible AI practice — bias, fairness, and system design
- Substantial portfolio project with regular one-to-one sessions
How it is structured:
Month 1–2: Advanced modelling and deep learning foundations
Month 2–3: Serving, deployment, and production monitoring
Month 3–4: Responsible AI practice and system design
Throughout: Portfolio project developed with mentor in regular 1:1 sessions
Decide What Fits
Which Course Is Right for You?
Use this comparison to find the course that matches where you are and what you want to work toward.
| What Is Included | AI Basics ฿1,950 |
Practical ML ฿6,300 Popular |
Full Track ฿12,500 |
|---|---|---|---|
| Structured lessons and practice notebooks | |||
| Mentor feedback on exercises | |||
| Portfolio project | Introductory | ||
| Group discussion sessions | |||
| One-to-one mentorship sessions | |||
| Code review on project | |||
| Deployment and monitoring content | |||
| Best for | Newcomers, career changers | Those with the basics, ready to go deeper | Committed learners preparing for professional work |
Across All Courses
Standards That Apply to Every Course
Privacy and Data Security
Learner information is stored securely and used only for course delivery and communication. See our Privacy Policy for full details.
Regular Curriculum Updates
Course material is reviewed quarterly and updated when tools, libraries, or best practices shift in meaningful ways.
Feedback Turnaround
Submitted work is reviewed by a mentor and feedback returned within three business days.
Responsible AI Throughout
Ethical considerations around AI systems are woven into all three courses rather than confined to a single optional section.
Small Cohort Policy
Cohorts are kept small so that mentor attention stays personal and discussion sessions remain substantive.
Accessible Support Team
The Samong team is reachable by email and phone during office hours for questions that arise between sessions.
Pricing
Clear Prices, No Hidden Costs
AI Basics for Beginners
฿1,950
per course (~8 weeks)
- Structured lessons and practice notebooks
- Mentor feedback on exercises
- Small introductory project
Practical Machine Learning
฿6,300
per course (~10–12 weeks)
- All AI Basics content plus deeper practice
- Real dataset exercises with mentor reviews
- Group discussion sessions
- Portfolio project with code review
Full AI Development Track
฿12,500
per course (several months)
- Full curriculum including deployment and monitoring
- Regular one-to-one mentorship sessions
- Code review throughout the project
- Substantial portfolio project
Not Sure Which to Choose?
Tell us a little about where you are and what you are hoping to build, and we will help you figure out the best place to start.
Send Us a Message