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Foundational Machine Learning

Understand, train, evaluate, and communicate a simple machine-learning model.

Format
Foundational technical course
Designed for
Students, analysts, and early-career professionals beginning applied machine learning

The program

An accessible technical foundation for students and early-career professionals. Learners work from a real question through data preparation, baseline modeling, evaluation, and responsible interpretation without treating model accuracy as the whole story.

You leave with

A documented baseline model and model card covering data, metrics, limitations, and next steps

Learning arc

  1. 01Problem framing and machine-learning task types
  2. 02Data quality, preparation, and leakage
  3. 03Features, baselines, and model training
  4. 04Evaluation metrics and error analysis
  5. 05Bias, overfitting, and responsible interpretation
  6. 06Model card and practical next-step plan
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