Three AI courses forming one learning path at Panya AI
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Three Courses,
One Clear Direction

The Panya AI curriculum moves from Python and AI fundamentals through practical model-building to advanced system design. Each programme builds directly on the previous one.

Our Approach

How the Curriculum Is Structured

Most AI courses treat each topic in isolation. Panya AI programmes are built around a single learning path: each course assumes and extends knowledge from the previous one. This means less repetition, less confusion about what level something is pitched at, and a clearer sense of progress.

Theory is covered concisely so that most time goes to writing and reviewing code. Weekly assignments are short enough to fit into a busy schedule but substantial enough to require genuine application of what has been covered. All work is reviewed by a named mentor.

1

Foundations of AI & Python

8 weeks · ฿4,500 · Beginner level

2

Applied Machine Learning

10 weeks · ฿9,800 · Intermediate level

3

Deep Learning & AI Systems

12 weeks · ฿18,000 · Advanced level

Weekly assignment rhythm

Each week closes with a practical assignment. Submission is followed by written mentor feedback, usually within two working days.

Code review at every stage

Applied ML and Deep Learning programmes include code reviews alongside assignment feedback, focusing on clarity, correctness, and engineering judgement.

Capstone portfolio project

Each programme closes with a substantial project that demonstrates the full range of skills from that level. Projects are designed to be kept and shown.

Foundations of AI and Python course
Level 1 · Beginner

Foundations of AI & Python

An entry-level programme covering programming fundamentals and AI thinking. You will study Python from the beginning, work with data, and explore core machine-learning concepts through guided projects. Designed for those new to the field who want a steady, well-paced start. Mentor feedback and a portfolio project are included across the eight-week programme.

Python syntax, data types, functions, and file handling
Data handling with NumPy and Pandas
Core ML concepts: regression, classification, evaluation
Mentor feedback on every assignment
Portfolio project: end-to-end ML pipeline
8 weeks Beginner
Level 2 · Intermediate Most Popular

Applied Machine Learning

A practical intermediate programme focused on building and evaluating models with real datasets. You will work through common supervised and unsupervised algorithms, study model tuning and validation, and practise clean coding approaches. A good fit for those with basic Python knowledge. Includes weekly assignments, code reviews, and a capstone project across ten weeks.

Supervised learning: regression, decision trees, SVMs
Model evaluation, cross-validation, and metrics
Feature engineering and data preprocessing
Weekly code reviews from a named mentor
Capstone: full modelling pipeline on a real dataset
10 weeks Intermediate
Applied Machine Learning course
Deep Learning and AI Systems course
Level 3 · Advanced

Deep Learning & AI Systems

An advanced programme covering neural networks, model deployment, and the design of complete AI systems. You will build and ship a substantial project with mentor support, exploring architecture decisions, training strategies, and evaluation at scale. Suited to those with prior machine-learning experience. Runs across twelve weeks with regular guidance sessions.

Neural network design and architecture choices
Training, regularisation, and debugging strategies
Model deployment and system integration
Regular mentor guidance throughout
Capstone: complete AI system from design to deployment
12 weeks Advanced

Which Course Is Right for You?

Use this table to identify where you fit in the pathway and what is included at each level.

Feature Foundations Applied ML Deep Learning
Duration 8 weeks 10 weeks 12 weeks
Prior Python needed
Mentor feedback
Code review
Portfolio project
Price ฿4,500 ฿9,800 ฿18,000

Standards Across All Programmes

These apply at every level, regardless of which course you are enrolled in.

Data Privacy

Student data and submitted work are stored securely and never shared outside the school.

Current Content

Courses are reviewed and updated twice each year to reflect changes in tools and practice.

Direct Support

All queries go to a person who knows the material — response within two working days.

Peer-Reviewed Lessons

Every lesson in the curriculum is checked by a second practitioner before it goes live.

Not Sure Where to Begin?

Send us a message with a brief description of your background and what you want to build. We will suggest the most appropriate starting point.

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