Data Science includes the technologies and techniques for data analysis and processing. Data, referred to as the oil of the 21st century, is the foundation for Machine Learning. This is the branch of Artificial Intelligence that deals with the study of algorithms and techniques that improve in an automated way thanks to the exploitation of data. In the course we will get to know the basic tools and principles for exploiting data with Data Science and Machine Learning technologies, as it can be applied to real problems. We will cover a wide range: We will start from raw data analysis and processing, a prerequisite and first step in any Machine Learning application. We will see how to visualize data so that on the one hand we can understand it better and on the other hand we know how it can be exploited. We'll discuss how we can learn from them using statistical methods – Machine Learning extends, not replaces, the data mining toolbox that statistics gives us when we apply it in practice. We will meet various Machine Learning methods with a wide range of applications, reaching up to Deep Learning technologies. Our vehicle will be the Python language, which is commonly used in Machine Learning. You don't need to be a keen programmer to learn about Applied Machine Learning. A familiarity with Python, an open mind, an appetite for learning tools, and above all a willingness to rub with the object, can open the door to a field that has changed, is changing, and will increasingly change our lives.
