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Each round has its own curriculum. More advanced rounds include everything from the previous rounds, so students build depth step by step across the full olympiad pathway.

The curriculum progresses across three stages: Qualification Round, National Round and Final Round.

Top 4 students selected in the Final Round will form the UAE team for CEOAI 2026.

Stage 1

Qualification Round

Stage 1Online

The first online round focuses on Python foundations, data preparation and core supervised learning models.

Advancement

Top 120 students advance to the National Round.

This round introduces the core syllabus for the olympiad.

This is the starting round of the curriculum path.

1. Python foundations

  • Linear, iterative and decision structures
  • Lists and two-dimensional arrays
  • Functions
  • Classes
  • Reading, processing and displaying text files, CSV files and images

2. Data processing

  • Handling missing values
  • Normalization
  • Scaling

3. Supervised learning

  • Linear regression and logistic regression
  • Naive Bayes
  • Decision trees
  • Kernels: Support vector machines (SVM), Ridge and Perceptron
Stage 2

National Round

Stage 2Online

The second online round expands the syllabus with advanced supervised learning, unsupervised learning, NLP, computer vision and AI search.

Advancement

Top 25 students advance to the Final Round.

This round includes all Qualification Round topics, plus the following.

More advanced rounds include the curriculum from all previous rounds. It expands the Qualification Round syllabus with more advanced machine learning and AI problem-solving topics.

4. Supervised learning

  • Ensemble methods: Random forest, boosting, bagging and voting

5. Unsupervised learning

  • Clustering: K-nearest neighbors (kNN), K-means, DBSCAN and hierarchical clustering

6. Data processing

  • Dimensionality reduction

7. Natural Language Processing

  • Text processing
  • Word embeddings: Bag of Words (BOW) and Term Frequency-Inverse Document Frequency (TF-IDF)

8. Computer Vision

  • Image processing

9. AI search

  • Constraint Satisfaction Problems (CSPs)
  • State-space traversal: BFS and DFS
  • The A* algorithm and heuristics
  • The Minimax algorithm
Stage 3

Final Round

Stage 3GEMS School of Research and Innovation, Dubai, United Arab Emirates

The on-site Final Round at GEMS School of Research and Innovation in Dubai focuses on advanced NLP, computer vision, deep learning and reinforcement learning. The Top 4 students selected here will form the UAE team for CEOAI 2026.

Advancement

On-site round in Dubai at GEMS School of Research and Innovation. Top 4 students are selected for the UAE team at CEOAI 2026.

This round includes all Qualification Round and National Round topics, plus the following.

More advanced rounds include the curriculum from all previous rounds. It builds on both previous rounds before the final CEOAI 2026 team selection.

1. Natural Language Processing

  • Word2Vec, FastText and GloVe

2. Computer Vision

  • Image augmentations

3. Deep Learning

  • Neural network basics: Perceptron, MLP and backpropagation
  • Optimization techniques: SGD, Adam, RMSProp, learning rate schedules, regularization, dropout and batch normalization
  • Convolutional neural networks
  • Recurrent neural networks
  • Using pretrained models

4. Reinforcement Learning

  • Markov Decision Processes (MDPs)
  • Temporal Difference Learning
  • Q-learning