Machine Learning with Python – Foundations Course

This course is designed for beginners with basic programming skills who want to understand how Machine Learning works step by step and apply it in practice.
From data preparation and visualization to simple models, you will learn how a complete ML workflow is structured — clear, practical, and easy to follow.

You will work with real datasets, use Jupyter Notebooks for reproducible analysis, and develop your own small ML project to deepen your understanding. 

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Who this course is designed for

  • Beginners with basic Python knowledge
  • People who want to understand how Machine Learning works in practice
  • Analysts, students, career changers
  • Teams that need ML fundamentals for later specialization

What you will learn in this course

  • Load, explore, and clean real datasets using pandas
  • Visualize data with Matplotlib and identify patterns
  • Train and evaluate simple ML models for regression, classification, and clustering
  • Understand and apply core ML concepts such as features/labels, train/test split, overfitting
  • Build complete workflows using scikit-learn pipelines
  • Develop your own small ML project, document it, and present it

Course Information

  • Duration: 5 days (extendable to 8 with optional modules)
  • Format: In-person or live online
  • Methodology: 30% theory, 50% hands-on, 20% project
  • Tools: Python 3.9+, pandas, NumPy, Matplotlib, scikit-learn
  • Group size: Small groups for personal feedback

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