This course will take you from Python basics to exploring different types of data. You will learn how to prepare data for analyses, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more.
This course provides you with the major steps involved in tackling a data science problem and practicing data science, with interesting real-world examples at each step – forming a concrete business or research problem, collecting and analyzing data, building a model, and understanding the feedback after model deployment.
This course dives into the basic of machine learning using Python, an approachable and well-known programming language. You will learn about supervised and unsupervised learning, analyze the relation between statistical modelling and machine learning through comparisons.
Get a crash course on the what there is to learn and how to go about learning more. Deep Learning presents a simplified explanation of some of the hottest topics in data science today.