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Preparing for AI Olympiads

Training overview

Build the foundations to work with data, train models and solve AI problems. Here is a suggested path and material you can explore today.

Where to begin

Start with Python if you are new to programming. If you already code, focus on the mathematics and model evaluation you need next.

Go to learning resources
  1. Python & data

    Functions, arrays and data handling. Load a dataset, inspect it and write a reliable baseline.

    Try it: Load a small CSV, identify missing values and calculate a summary for each column.

  2. Mathematics

    Linear algebra, probability and statistics. Understand the calculations behind your models.

    Try it: Calculate a dataset’s mean and variance, then check your calculations in Python.

  3. Machine learning

    Regression, classification and validation. Compare models without leaking test data into training.

    Try it: Split a dataset into training and validation sets. Compare a simple baseline with a classifier using the same metric.

  4. Deep learning

    Neural networks, computer vision and language. Train, evaluate and improve models for more complex tasks.

    Try it: Train a small image classifier and inspect its mistakes. Compare its results with your baseline.

Train with MOAI

Lessons, practice problems and contests are being prepared. The MOAI platform is not open yet.

Olympiad platformComing soon
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