Machine Learning 101

This course takes you from the fundamentals of Machine Learning to advanced, real-world applications. You’ll learn what Machine Learning really is, the math and logic behind it, and how to build models that can learn, adapt, and make intelligent decisions. We’ll cover the core pillars like supervised, unsupervised, and reinforcement learning along with the complete ML workflow: from collecting and cleaning data, to training and evaluating models, to deploying them in real-world systems. You’ll explore real use cases like recommendation engines, fraud detection, predictive analytics, and self-driving technology. By the end of this course, you won’t just “know about” Machine Learning, you’ll be able to think like a machine learning engineer, understand the trade-offs behind different approaches, and apply ML techniques to real projects. This course is built for curious beginners, ambitious developers, and anyone who wants to future-proof their skills in the age of AI.