This Machine Learning Fundamentals course is designed to give you a solid foundation in machine learning concepts and practical techniques. Whether you're new to AI or looking to strengthen your data science toolkit, this course walks you through the key steps of building intelligent systems.

You will learn to:

• Understand the difference between supervised and unsupervised learning

• Explore popular algorithms like linear regression, decision trees, and k-means clustering

• Preprocess and clean data for machine learning workflows

• Train, test, and evaluate models using Python and libraries like scikit-learn

• Apply ML to solve real-world problems through hands-on projects

With easy-to-follow lessons, real datasets, and practical examples, you'll gain both the confidence and skill set needed to continue your journey into AI, data science, or advanced machine learning topics.