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Beginner

Levels 1 – 3

Supervised vs unsupervised learning, linear regression, classification, and evaluation metrics.

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Intermediate

Levels 4 – 6

Feature engineering, ensemble methods, neural network basics, and model selection.

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Advanced

Levels 7 – 10

Deep learning architectures, NLP, computer vision, MLOps, and distributed training.

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