Codexis
Codexis AI learning tracks overview

Three Tracks

From First Script
to AI System Design

A complete curriculum path across three courses — each a deliberate step from the one before, each ending with work you can keep.

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Our Methodology

How Every Codexis Track Is Built

The same design principles apply across all three tracks — staged modules, mentor feedback, real practice, and a tangible output at the end.

Staged Modules

Each module builds on the previous. Prerequisites are clearly stated. No skipping ahead.

Practice First

The ratio of exercises to reading is weighted toward doing. You write code, clean data, and build things at every stage.

Mentor Feedback

Submitted work is reviewed by a human. Feedback is specific to what you wrote, not generic automated output.

Portfolio Output

Every track ends with something you own — reviewed code, end-to-end project work, or a system design portfolio.

Programming for AI Track

Process Steps

  1. 01

    Setup and orientation — Python environment, tooling, and working habits

  2. 02

    Core programming concepts — data types, control flow, functions, modules

  3. 03

    Data handling — NumPy, Pandas, and working with structured datasets

  4. 04

    Starter portfolio compilation — review and consolidation of exercise work

Beginner Track 01

Programming for AI Track

A structured introduction to the programming and data skills that underpin AI work, with mentor guidance and weekly exercises. Designed for learners who are starting from scratch with code and data — and who are willing to put in consistent effort over the duration of the track. Includes a small starter portfolio of reviewed work.

  • Suitable for learners with no prior programming background
  • Weekly exercises reviewed by mentor with written feedback
  • Focus on data types and operations relevant to ML
  • Starter portfolio at track completion
  • Approximate weekly commitment: 6–8 hours
฿4,000 Enquire About This Track
Machine Learning Project Course

Process Steps

  1. 01

    Data sourcing and cleaning — real datasets with missing values and noise

  2. 02

    Exploratory analysis — understanding data before modelling

  3. 03

    Model selection, training, and evaluation — supervised learning methods

  4. 04

    Code review sessions with mentor feedback on each project

  5. 05

    Final project compilation — reviewed body of ML work

Most Popular Track 02

Machine Learning Project Course

A practical course focused on building end-to-end models on real datasets, with code review sessions and mentor feedback at each stage. Suited to learners who have basic programming skills and want to move into applied machine learning. The course produces a tangible body of project work that reflects actual capability.

  • Requires basic Python proficiency before starting
  • End-to-end project flow: data → model → evaluation
  • Mentor code review on every submitted project
  • Multiple project types: classification, regression, NLP basics
  • Approximate weekly commitment: 10–15 hours
฿16,500 Enquire About This Track
Advanced AI Systems Track

Process Steps

  1. 01

    AI system architecture — design patterns and component relationships

  2. 02

    Model refinement — evaluation methods, iteration approaches, debugging

  3. 03

    Peer collaboration projects — working with others on shared AI tasks

  4. 04

    Deployment considerations — practical constraints of real-world AI systems

  5. 05

    Portfolio compilation — advanced system design and implementation work

Advanced Track 03

Advanced AI Systems Track

A deep programme on designing, building, and refining AI systems, with peer collaboration and ongoing mentorship. The focus is on real-world practice at a level of complexity that requires consistent effort and prior machine learning experience. This track is not a shortcut — it rewards learners who show up and do the work.

  • Requires machine learning experience before starting
  • System-level thinking: architecture, trade-offs, constraints
  • Peer collaboration sessions built into the track
  • Mentorship throughout, not just at submission points
  • Approximate weekly commitment: 12–18 hours
฿33,000 Enquire About This Track

Choose Your Path

Track Comparison

Not sure which track to start with? Use this table to compare what each one covers and what it requires.

Feature Programming Track
฿4,000		 ML Project Course
฿16,500		 Advanced AI Systems
฿33,000
Prior experience needed None Basic Python ML experience
Weekly time commitment 6–8 hrs 10–15 hrs 12–18 hrs
Mentor code review
Real datasets
End-to-end ML projects —
AI system design — —
Peer collaboration — —
Portfolio output Starter Project body System portfolio

Best for: Programming Track

You want to learn Python and data skills from the beginning, with guidance and a clear path forward.

Best for: ML Project Course

You can write Python and want to build real machine learning projects with feedback.

Best for: Advanced Systems

You have ML experience and want to work at the level of system design and real-world deployment challenges.

Shared Standards

What Every Track Has in Common

Privacy and Data Security

Learner submissions and personal data are handled under a clear privacy policy. Course work is not shared externally.

Regular Content Review

Track content is reviewed on a scheduled cycle. Libraries, approaches, and examples are updated when the field moves.

Browser-Based Access

All course content is accessible from a standard browser. No proprietary platform software required for any track.

Written Feedback Records

Mentor feedback is written and stored. Learners can review earlier comments throughout the course.

Transparent Terms

Refund terms and enrolment conditions are in the Terms and Conditions — readable before purchase, with no surprises.

Support Response SLA

Questions go to the team directly. Response time target is one business day during Monday–Friday office hours.

Pricing

Course Fees in Thai Baht

One-time payment per track. No subscription, no renewal, no hidden fees. All tools used in the course are freely available.

Track 01

Programming for AI

Beginner · Self-paced · Mentor-reviewed

฿4,000 one-time
  • Full track access
  • Weekly exercise review
  • Starter portfolio output
  • Support access
Enquire
MOST POPULAR

Track 02

Machine Learning Projects

Intermediate · Self-paced · Code reviews

฿16,500 one-time
  • Full track access
  • Mentor code review per project
  • Multiple project types
  • Project body portfolio
  • Priority support access
Enquire

Track 03

Advanced AI Systems

Advanced · Cohort-based · Peer + mentor

฿33,000 one-time
  • Full track access
  • Ongoing mentorship
  • Peer collaboration sessions
  • Advanced system portfolio
  • Priority support access
Enquire

Enrol or Ask a Question

Not Sure Which Track to Start With?

Describe your background and we will give you an honest recommendation — no pressure, just a straightforward answer.

Talk to the Team