CJAIO National Qualifier
CJAIO National Qualifier consists of two rounds designed to evaluate both theoretical understanding and practical skills in AI.
Part 1: AI Fundamentals & Computational Thinking Challenge
Participants will solve a series of programming, algorithmic, mathematical, data science, and introductory machine learning problems. Questions are designed to assess both conceptual understanding and practical problem-solving skills, including code tracing, code completion, numerical calculation, data interpretation, and reasoning about basic AI and machine learning models.
- Format: 12 single-choice questions (2 marks each), 6 multiple-select questions (4 marks each), 4 short-answer questions (5 marks each), and 4 advanced short-answer questions (8 marks each)
- Programming Language: Python
- Total Score: 100
- Duration: 60 minutes
- Focus: Python programming fundamentals, core data structures, algorithmic thinking, computational problem solving, mathematical foundations for AI, data literacy and processing, data visualization and interpretation, introductory machine learning concepts, and basic machine learning models such as Linear Regression, Logistic Regression, Decision Trees, K-Nearest Neighbors (KNN), and K-Means Clustering.
Part 2: Applied Data Science & Machine Learning Challenge
Participants will work with a real-world-style dataset that may contain missing values, inconsistent formats, duplicate records, multiple related tables, and other data quality issues. Using Python in Google Colab, participants will explore, clean, transform, integrate, and analyze the data before applying appropriate introductory machine learning techniques to complete a regression or classification task.
The challenge emphasizes the complete data science workflow—from understanding and preparing raw data to extracting meaningful insights and building a functional predictive model.
- Format: One practical, computer-based data science and machine learning problem
- Programming Language: Python
- Environment: Google Colab
- Total Score: 100
- Duration: 60 minutes
- Focus: Exploratory data analysis (EDA), data cleaning, data integration and merging, missing-value handling, duplicate detection, data type and format standardization, data transformation, summary statistics, data visualization, feature preparation, and introductory machine learning
- Machine Learning Tasks: Participants may be asked to build a simple regression or classification model using appropriate algorithms covered in the CJAIO syllabus
- Evaluation Criteria: Correctness and quality of data preprocessing and analysis, effectiveness of data visualization and interpretation, appropriate application of machine learning methods, model performance, and clarity and organization of code
- Note: This is an online competition. Participants must use their own computers and maintain a stable internet connection throughout the competition. Only approved webpages and resources may be accessed. Detailed competition instructions will be released before the competition, and the use of AI tools such as ChatGPT or similar services is strictly prohibited.
CJAIO National Training Camp
1. The invite-only National Training Camp, open to the top 20 contestants from the CJAIO National Qualifier, will begin with three full days of intensive in-person training on November 28, November 29, and December 5, 2026. The training will be followed by a two-part Canadian National Team Selection Competition. The top four contestants will be invited to join the 2026–27 CAIO National Training Camp.
2. The program will feature lectures and intensive training sessions led by university professors specializing in artificial intelligence, as well as experts from leading technology companies.
3. The National Team Selection Competition will follow a format similar to the CJAIO National Qualifier, while featuring more challenging problems designed to further develop and assess participants’ skills. Each part of the competition will last two hours.