About This Course

Machine Learning is the science of teaching computers to learn from data and make decisions without being directly programmed. In this course, you'll explore how machines can solve problems like humans — identifying patterns, predicting future outcomes, and improving with experience. Through simple explanations and real-life examples (like how YouTube recommends videos or how Google Maps finds the fastest route), you’ll learn about different types of machine learning: supervised learning (learning from labeled data), unsupervised learning (finding hidden patterns), and reinforcement learning (learning through trial and error).

The course focuses on building strong foundational knowledge without needing a programming background. You'll discover popular algorithms such as linear regression, decision trees, and clustering, and understand when and why to use them. With plenty of visuals, storytelling, and hands-on activities, you'll learn not just what machine learning does, but how it can be applied in business, healthcare, education, and beyond. This is the perfect first step into the world of AI and data science.