The Algerian Olympiad in Artificial Intelligence
AOAI Mission
The Algerian Olympiad in Artificial Intelligence (AOAI) aims to identify, train, and empower the nation’s most talented young minds in AI, preparing them to represent Algeria at the International Olympiad in Artificial Intelligence. Through rigorous selection, mentorship, and innovation-driven learning, AOAI fosters excellence and inspires the next generation of AI leaders.
Why Join Us ?
Math
Strengthen your AI-ready math skills.
Programming
Learn to code smart solutions.
Problem Solving
Think critically, solve creatively.
Upcoming Events
AOAI Genesis
AOAI Ascend
AOAI Vanguard
AOAI Apex
AOAI Zenith
Official Selection Process
The Algerian Olympiad in Artificial Intelligence (AOAI) selection process is designed to identify, train, and prepare the most promising students to represent Algeria at the international level, particularly at the International Olympiad in Artificial Intelligence (IOAI).
Season 2 is structured into five progressive stages — Genesis, Ascend, Vanguard, Apex, and Zenith — moving from foundational reasoning and independent learning towards full national-team representation.
As the season progresses, training increasingly follows the official IOAI syllabus, while the expected level of independence, problem-solving ability, and commitment rises at each stage.
Results for every round are published publicly on the AOAI website and the Discord server.
Everything in AOAI is completely free — students never have to pay for anything. Note that dates and scheduling depend on the official school calendar published by the Ministry of National Education and may change accordingly. This outline, including the number of participants progressing at each stage, is subject to change throughout the season.
AOAI Genesis
Period: EduSpace Round 1 - To Be Announced · Coding Test — October 10, 2026
The first stage measures how well participants reason, adapt, and learn independently when faced with concepts they have not seen before — not how much they already know about AI.
Eligibility
- Algerian citizenship
- Under 19 years old
No separate registration process — taking part in Round 1, which is public and open to everyone, registers you automatically.
Format
- EduSpace Round 1, To be Announced
- Coding Test — October 10, 2026, 5 hours, on a form we provide, where you upload your solutions
- Completed independently — no help from other participants or outside tools
Roughly 50% of participants advance to AOAI Ascend.
What's Tested
Each test is built around:
General AI Literacy (MCQ)
General AI literacy and basic everyday information — delivered as multiple choice on EduSpace.
Programming (Coding Test)
Python problems drawn from Machine Learning, Computer Vision, and NLP pipelines, submitted through the form we provide.
Prior Knowledge
Not required. Every problem introduces the concepts and definitions needed to solve it — the test measures how fast you learn, not what you already know.
For a full breakdown of preparation resources, download the AOAI Genesis guide:
Download PDF GuideRules
The use of any Artificial Intelligence tool is strictly forbidden — including LLMs, AI-powered code completion, and AI assistants built into editors, whether accessed online or run locally.
AOAI Ascend
Period: During the academic year
The second stage shifts from foundations to real machine-learning problems, with participants expected to grow steadily more independent in acquiring whatever each new problem requires.
Core Training
- Data cleaning, preprocessing, and exploratory data analysis
- Feature engineering, model construction, training, and evaluation
- Learning to identify and evaluate documentation, tutorials, and papers independently
Tooling
- NumPy and SciPy for numerical computing
- Pandas for data manipulation and analysis
- Scikit-learn, XGBoost, and CatBoost for practical ML models
Selection Test
Round 2 combines a written mathematics test with a basic Machine Learning problem on tabular data.
AOAI Vanguard
Period: During the academic year
The third stage begins the deep-learning track with PyTorch — the framework used at the IOAI — and is where training starts following the official IOAI syllabus directly.
Focus Areas
- Natural Language Processing and Computer Vision — full data pipelines, from raw data to model input
- Model architecture, activation and loss functions, optimization, and training loops
- Reading and analyzing the research papers behind modern models, not just using them
Working With Models
- Using existing, pretrained architectures under real time and resource constraints
- Transfer learning, fine-tuning, and architectural adaptation
- Regular mock contests based on past Olympiad-style problems and national selection programs
There is rarely one model or configuration that is optimal for every problem.
Selection Test
Round 3 covers Computer Vision and Natural Language Processing problems.
AOAI Apex
Period: End of the academic year
The final selection stage consolidates everything learned so far and introduces the last areas of the IOAI syllabus, including audio tasks and the Hugging Face ecosystem.
Focus Areas
- Completing the remaining IOAI syllabus, including audio-related tasks
- Selecting, loading, and fine-tuning pretrained models through the Hugging Face ecosystem
- Combining every previous skill into complete, end-to-end competition solutions
Preparation
- Solving past IOAI tasks and other difficult Olympiad-style problems
- Working under realistic time pressure and decision-making constraints
Four students from Season 1 are exempt from earlier stages and enter directly here: Mohamed Alaa eddine Khelifi, Rostom Mohamed Kamel Bouabdallah, Nesrine Mazouz, and Sofiane Bouricha.
Final Team Selection Test
Round 4 draws on the entire IOAI syllabus — any topic covered so far is fair game. Ten participants compete under conditions that mirror the real IOAI: analyzing unfamiliar problems, using available tools and models effectively, managing time, and debugging under pressure.
AOAI Zenith
Period: IOAI 2027 — Singapore
AOAI Zenith is reserved for the four students selected to officially represent Algeria at the International Olympiad in Artificial Intelligence.
Our Expert Coaches
Learn from the best minds in Algerian AI
Ilyes Mohammed LAKHAL
Head Coach
Research Fellow in computer vision and Deep learning
Mohammed Hachem DRICI
Coach
Computer Science Student in in UEHL
Raouf OULD ALI
Coach
AI student in ENSIA
Zakaria HAMMAL
Coach
Computer Science Student in USTHB
Ali BEN CHIKH
Coach
Graduate in Applied Mathematics University of Tamanghasset
Mohammed Al Ghazali MEGHABBER
Coach
AI Student in ENSIA
Zakaria Ahmed LAHCINE
Coach
Electrical Engineering Student in INELEC
Redhouane ABDELLAH
Coach
IOI participant, computer science student at esi-sba
Rayan OUALI
Coach
2CP, ENSIA
Our Ambassadors
Meet our dedicated AI ambassadors across Algeria
Merouane Debah
Director of the KU 6G Research center
Professor at Khalifa University
Our Valued Sponsors
Supported by leading organizations in AI and technology
Platinium Sponsors
