Learn Spark

"Learn Spark" is a comprehensive online course designed to help individuals learn the basics of Apache Spark, one of the most popular open-source big data processing frameworks. The course covers a wide range of topics, from the basics of Spark to more advanced concepts like streaming, machine learning, and graph processing. It is structured in a way that allows learners to progress at their own pace, with each section building on the previous one. The course starts with an overview of Spark and its key features, including its distributed computing architecture, resilient distributed datasets (RDDs), and Spark SQL. Learners then move on to explore Spark's various APIs, including the RDD, DataFrame, Dataset, and Spark Streaming APIs. The course also covers more advanced Spark topics like machine learning, graph processing, and Spark on Kubernetes. In the machine learning section, learners are introduced to Spark's machine learning library (MLlib) and learn how to use it to build and train various machine learning models. In the graph processing section, learners explore Spark's GraphX API and learn how to use it to analyze and visualize graph data. The course also covers how to deploy Spark on Kubernetes, which allows learners to run Spark in a containerized environment. Throughout the course, learners get hands-on experience working with Spark using the Apache Spark Notebook, a web-based interactive development environment (IDE) for Spark. They also have access to a range of practice exercises and quizzes to reinforce their learning. By the end of the "Learn Spark" course, learners will have a solid understanding of Spark and its various APIs and be able to use Spark to build data processing applications. They will also have experience working with Spark's machine learning and graph processing libraries and have a solid understanding of how to deploy Spark on Kubernetes. Whether you are a data engineer, data scientist, or software developer, "Learn Spark" is an excellent course to help you get started with Spark and take your big data processing skills to the next level. Author: David Drummond, Judit Lantos (Udacity)