How the Curriculum Works
Tensora's curriculum is built in layers that deliberately connect. The Intro course teaches Python and data concepts in the same way they appear in the Machine Learning course. The Machine Learning course uses frameworks and patterns that form the foundation of the Engineering Track.
Rather than standalone units, each course is written knowing what comes before and after it. This means learners who move through all three layers do not need to relearn or bridge concepts — progress carries forward cleanly.
Guided fundamentals
Concepts are introduced with explanation, shown in working code, and then applied in a small project — every lesson follows this sequence.
Build sessions
Regular project sessions give learners time to put concepts to use in a supervised but open-ended environment.
Mentor review
Work is reviewed by a named mentor who provides specific written and verbal feedback based on what you have submitted.
Layer completion
Each course ends with a capstone or final project, a completion review with your mentor, and a certificate documenting the skills covered.
Intro to Applied AI
A friendly introductory course covering Python essentials, working with data, and core ideas behind modern models. Designed for newcomers wanting a calm, structured start. Includes guided lessons, small practice projects, mentor-supported feedback, and a certificate of completion.
How it runs:
Hands-On Machine Learning
A project-based course exploring model training, common frameworks, and real datasets through guided builds. Suited to learners with basic Python seeking practical experience. Includes weekly build sessions, code reviews, a capstone project, and community access.
How it runs:
Applied AI Engineering Track
An extended program covering model development, deployment practices, and collaborative workflows, with portfolio building throughout. Aimed at committed learners preparing for technical roles. Includes mentor guidance, applied projects, peer collaboration, and skills-focused career sessions.
How it runs:
Choosing the Right Course
Use this table to see which course fits where you are right now.
| What you want | Intro | ML Course | Eng Track |
|---|---|---|---|
| Start from zero with no prior code experience | — | — | |
| Already know Python basics, want ML practice | — | — | |
| Preparing for a technical AI or data role | — | — | |
| Certificate of completion | |||
| Portfolio of real projects | — | Capstone | |
| Career-focused sessions | — | — |
Not sure which layer to start? Get in touch and we will help you decide.
Shared Across All Three Courses
Data Privacy (PDPA)
Learner data is handled in line with Thailand's Personal Data Protection Act across all courses.
Qualified Mentors
All mentors have relevant technical backgrounds and complete an internal review process before joining.
Regular Content Updates
Curriculum is reviewed every six months to reflect changes in tools, techniques, and industry practice.
Project-Based Assessment
Assessment is built around what learners build — reviewed by mentors against published rubrics in every course.
Clear Course Fees in Thai Baht
Intro to Applied AI
8-week course · One fee
- All lessons and materials
- Mentor feedback sessions
- Certificate of completion
Hands-On ML
12-week course · One fee
- All lessons and materials
- Weekly build and code review sessions
- Capstone project + community access
- Certificate of completion
AI Engineering Track
6-month program · One fee
- All lessons, projects, and materials
- Mentor guidance and career sessions
- Portfolio of applied projects
- Certificate of completion
Not Sure Where to Begin?
Tell us a little about your background and what you're hoping to build — we'll point you to the right layer.
Get in Touch