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Machine Learning Fundamentals: From Theory to Practice

Machine Learning Fundamentals: From Theory to Practice

Core machine learning algorithms, data preprocessing, model evaluation, scikit-learn, neural network basics, and practical projects with real-world datasets
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Last Update 04/08/2026
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  • Introduction to Machine Learning
    5Lessons ·
    • What is Machine Learning?
    • What is Machine Learning? - Quiz
      10 xp
    • Supervised vs Unsupervised Learning
    • Key Terminology in Machine Learning
    • Real-World Applications of Machine Learning
  • Data Preprocessing Techniques
    4Lessons ·
    • Data Cleaning Basics
    • Handling Missing Values
    • Outlier Detection and Treatment
    • Data Normalization and Standardization
  • Core Machine Learning Algorithms
    4Lessons ·
    • Linear Regression
    • Decision Trees
    • Ensemble Methods - Random Forest
    • Model Evaluation Techniques
  • Introduction to Neural Networks
    4Lessons ·
    • Neural Network Architecture
    • Building a Simple Neural Network
    • Training and Evaluating Neural Networks
    • Applications of Neural Networks
  • Capstone Project
    4Lessons ·
    • Project Selection and Planning
    • Data Collection and Preprocessing
    • Model Development and Evaluation
    • Project Presentation and Reflection