Big Data has gained significant attention in recent years and has now become a mainstream concept for many companies. This course aims to provide a comprehensive understanding of Big Data through the use of PySpark. PySpark is a high-performance cluster computing framework designed specifically for handling large-scale data. It offers a versatile data processing platform that enables programs to run up to 100 times faster in memory or 10 times faster on disk compared to Hadoop. Throughout this course, you will learn how to utilize PySpark, a Python package for Spark programming, along with its powerful libraries such as SparkSQL and MLlib. These libraries enable advanced data analysis techniques, including machine learning, making it possible to extract valuable insights from complex datasets. To apply these concepts, you will work on various practical examples, including analyzing the works of William Shakespeare, examining Fifa 2018 data, and performing clustering on genomic datasets. By the end of this course, you will have developed a deep understanding of PySpark and its practical application in conducting comprehensive analysis of Big Data.