Introduction

Course overview

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this course, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you'll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems.

This course is designed to give you in-depth knowledge of Machine Learning concepts including the essentials of statistics required for Data Science, Python programming, and Machine Learning. Through these AI courses, you will learn how to use Python libraries like NumPy, SciPy, Scikit-learn, and essential Machine Learning techniques, including supervised and unsupervised learning.