Machine Learning for Beginners: From Concepts to Code

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About Course

Unlock the power of data with this beginner-friendly introduction to Machine Learning. In this course, you’ll learn the core concepts behind how machines learn from data — from simple algorithms to real-world applications. Using Python and libraries like scikit-learn, you’ll gain hands-on experience building models for classification, prediction, and clustering. No prior experience in AI or data science is required — just a passion for learning and a willingness to code!

What Will You Learn?

  • Understand the basic concepts of Machine Learning and its types
  • Work with real-world datasets for training and testing models
  • Apply supervised learning algorithms (like Linear Regression, Decision
  • Trees)
  • Explore unsupervised learning (like K-Means Clustering)
  • Use Python libraries like NumPy, Pandas, and scikit-learn
  • Evaluate model accuracy and avoid overfitting
  • Build and deploy simple ML models step-by-step
  • Understand ethical AI and responsible data usage

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