Courses

Course Tracks

Three practical paths: Junior for grades 6-8, Senior for grades 9-11, and an intensive group for stronger students preparing for selection and international tasks.

For Beginners

Junior Track

Start your AI journey from scratch. Learn Python programming fundamentals, mathematics for AI, and build your first introductory machine learning models.

Best for: Grades 6-8, beginners or early programmers.
Workload: Steady weekly practice with guided homework.
Outcome: Python confidence, math base, and first ML projects.

Python ProgrammingMathematics for AIIntro to Machine Learning

For Advanced Students

Senior Track

Deepen your training in ML, NLP, computer vision, reinforcement learning, and competitive AI problem solving.

Best for: Grades 9-11 with Python or olympiad experience.
Workload: More demanding tasks, labs, and regular checkpoints.
Outcome: Competition-ready ML foundations and stronger problem solving.

Machine LearningNatural Language ProcessingComputer VisionReinforcement LearningCompetitive Programming Algorithms

For Strong Students

National-Team Intensive

A focused preparation group for students who already solve technical problems confidently and need faster olympiad-style practice.

Best for: Students already performing above the regular cohort pace.
Workload: High workload, mock contests, review sessions, and fast feedback.
Outcome: Readiness for selection rounds, team practice, and international-style tasks.

Machine LearningNatural Language ProcessingComputer VisionCompetitive Programming Algorithms

Who teaches

A mentor team with olympiad background

Students work with instructors who have represented Kyrgyzstan in AI, informatics, and mathematics competitions.

Iskhak Tazhibaev

AI olympiad mentor

Matvey Nizovsky

AI olympiad mentor

Adil Kanatbekov

Informatics mentor

Aidin Asankadyrov

Mathematics and olympiad mentor

Akniet Kenzhegulov

AI practice mentor

Zhanibek Kasymkan

AI olympiad mentor

View mentors

Course Format

The curriculum runs as a blended cohort with recurring theory sessions, hands-on labs, and weekly quizzes.

2 theory sessions per week

1 hands-on lab per week

1 quiz per week

Blended cohort-based training

Topics Covered

Python Programming

Mathematics for AI

Machine Learning

Natural Language Processing

Computer Vision

Reinforcement Learning

Competitive Programming Algorithms

Enrollment and availability

Public pricing has not been announced. Contact the team for current group availability, entry requirements, schedule, and enrollment details.

Contact the Team