First AI Online IT School for the New Generation
Not just courses, but a managed learning system: personalized assignments, instant verification, structured feedback and transparent progress for each student. You learn, the system handles the routine.
Assessment
AI Rubric 100/100
Mode
24/7 Progress Sync
KNOWLEDGE
UI/UX/PD Design · Web · Mobile · AI
Special discount 30% for KadorrGroup residents — contact us on Instagram.
AITLab — Hero Video #1
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Core Experience
Learning built as a managed cycle, not chaotic lessons
Each stage is connected to the previous one: lesson topic → practice → homework → AI-check → recommendations for the next step.
01. Lesson + Practice
Student receives structured material and immediately reinforces the topic through real tasks.
- • Unified standard for all groups
- • Examples from real products
- • Tasks close to working scenarios
02. Homework + Auto-check
After submission, the system immediately returns the grade, errors and specific improvement points.
- • Transparent rubric for 100 points
- • Clear reasons for the grade
- • Recommendations without “water”
03. Personal Tasks “On the Go”
When more practice is needed — student requests a topic and receives a new task for their level.
- • For current difficulty level
- • For chosen career track
- • With progress tracking in the system
Career Tracks
Three trajectories, one growth system
Students learn to think product-wise, work systematically with tools and build portfolios of solutions, not just “go through lessons”.
UI/UX / Product Designer
From research to thoughtful interfaces and cases that can actually be shown to clients.
- • Product thinking and user flow
- • Design systems and UI quality
- • Solution presentation and argumentation
Web Development
Building modern products: React/Next.js, API architecture, production approach.
- • Component frontend
- • Backend routes and integrations
- • Code quality and deployment flow
AI / LLM Engineer
Practice with LLM: prompting, agents, evaluation and implementation in digital products.
- • Agent architecture
- • Tooling, pipelines, automation
- • Quality metrics and risk control
AI Assignment Engine
Examples of tasks generated by AI
This is a demonstration of the format: different tracks, difficulty levels and clear quality criteria.
Показано випадкові приклади
Evaluation suite для AI-грейдера
Підготуйте набір тестів для перевірки стабільності AI-грейдера: нормальні кейси, крайні сценарії та спроби prompt injection. Для кожного вкажіть очікуваний результат.
- • Good / edge / abuse матриця кейсів
- • Очікувані діапазони оцінок
- • Критерії стабільності та відмовостійкості
Prompt design: rubric-based оцінювання відповіді
Напишіть промпт для оцінювання студентської відповіді за рубрикою на 100 балів з поверненням суворого JSON: score, strengths, gaps, next_steps.
- • Суворий JSON без markdown-обгорток
- • Критерії, ваги, пороги якості
- • Приклади good / weak / abuse inputs
Редизайн екрана входу: нульова фрустрація користувача
Спроєктуйте оновлений flow входу: стани default/loading/error/success, підказки та доступність. Поясніть, як рішення знижує кількість помилок.
- • 4 стани інтерфейсу з чіткою логікою
- • Мікротексти, які ведуть, а не карають
- • Контраст, фокус, клавіатурна навігація
Community & Process
Live learning context
Real photos and videos of the environment where students work, present and grow.
Operations Layer
System that scales without chaos
Administrator manages rules and accesses, and operational processes the platform performs automatically and predictably.
Gemini AI engine generates relevant tasks, evaluates works according to the rubric and forms personal improvement steps.
Roles, accesses, payment statuses and discounts are managed through Google Sheets, without separate CRM routine.
Start Here
Ready to connect to AITLab?
If you already have login — enter the dashboard. If not — write to us on Instagram, we'll select a group, track and starting learning plan.