The editors at Solutions Review have compiled this list of the best Apache Spark courses on Udemy to consider if you’re looking to grow your skills.
Apache Spark is a unified analytics engine for large-scale data processing. It is noted for its high performance for both batch and streaming data by using a DAG scheduler, query optimizer, and a physical execution engine. Spark offers more than 80 high-level operators that can be used interactively from the Scala, Python, R, and SQL shells. The engine powers a stack of libraries including SQL and DataFrames, MLib for machine learning, GraphX, and Spark Streaming. Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud.
With this in mind, we’ve compiled this list of the best Apache Spark courses on Udemy if you’re looking to grow your skills for work or play. Udemy is one of the top online education platforms in the world with more than 130,000 courses, expert instruction, and lifetime access that allows you to learn on your own schedule. As you can see below, we broke the best Apache Spark courses on Udemy down into categories based on the recommended proficiency level. Each section also features our inclusion criteria. Click GO TO TRAINING to learn more and register.
Best Apache Spark Courses on Udemy for Beginners
Note: We included courses with more than 200 reviews and a rating of 4.3 stars or better.
Description: This course teaches you Apache Spark 2.0 with Java, trains you in building Spark analytics and machine learning programs, and helps you practice hands-on (2K LOC code samples) with an end-to-end real-life application project. The goal of this module is to provide hands-on training that applies directly to real-world big data projects. It uses the learn-train-practice-apply methodology as well. Taught by an expert in the field, you will also get a prompt response to your queries and excellent support from Udemy.
Description: In this course, you will learn how to write Spark Applications using Scala and SQL. The main focus of this module is to teach you how to use the DataFrame API and SQL to accomplish tasks like writing and running Apache Spark codes using Databricks and explain how Spark runs on a cluster with multiple nodes. This course is for software developers curious about big data, new data engineers, and new data scientists.
Best Apache Spark Courses on Udemy for All Levels
Note: We included courses with more than 1,000 reviews and a rating of 4.4 stars or better.
Description: This course is very hands-on; you’ll spend most of your time following along with the instructor as you write, analyze, and run real code – both on your own system and in the cloud using Amazon’s Elastic MapReduce service. Over 8 hours of video content is included, with over 20 real examples of increasing complexity you can build, run and study yourself. Move through them at your own pace, on your own schedule. The course wraps up with an overview of other Spark-based technologies, including Spark SQL, Spark Streaming, and GraphX.
Description: This course is very hands-on; you’ll spend most of your time following along with the instructor as we write, analyze, and run real code together – both on your own system, and in the cloud using Amazon’s Elastic MapReduce service. 7 hours of video content is included, with over 20 real examples of increasing complexity you can build, run, and study yourself. Move through them at your own pace, on your own schedule. The course wraps up with an overview of other Spark-based technologies, including Spark SQL, Spark Streaming, and GraphX.
Description: This course covers all the fundamentals of Apache Spark with Java and teaches you everything you need to know about developing Spark applications with Java. At the end of this course, you will gain in-depth knowledge about Apache Spark and general big data analysis and manipulations skills to help your company to adapt Apache Spark for building big data processing pipelines and data analytics applications. This module covers 10+ hands-on big data examples.
Description: Designed especially for Java developers, this course is a great way to get started with the Spark parallel computing framework. The module features All of the fundamentals you need to understand the main operations you can perform in Spark Core, SparkSQL, and DataFrames. You’ll be able to follow along with all of the examples and run them on your own local development computer. Also included with the course is a section covering SparkML, an exciting addition to Spark that allows you to apply machine learning models to your big data. No mathematical experience is necessary!
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