Cloudera Educational Services

DATE: May 7, 2026 9:00 - 17:00 (CEST TIMEZONE) Virtual Classroom, EMEA Read more

DO NOT START THIS CERTIFICATION EXAM HERE! Once you have been enrolled, you will receive an email with additional instructions to schedule your exam. If you click through this course and complete it you will not receive the email. Read more

This four-day hands-on training course delivers the key concepts and knowledge developers need to use Apache Spark to develop high-performance, parallel applications on the Cloudera Data Platform.  Hands-on exercises allow students to practice writing Spark applications that integrate with Cloudera Data Platform core components. Participants will learn how to use Spark SQL to query structured data, how to use Hive features to ingest and denormalize data, and how to work with “big data” stored in a distributed file system. After taking this course, participants will be prepared to face real-world challenges and build applications to execute faster decisions, better decisions, and interactive analysis, applied to a wide variety of use cases, architectures, and industries. Download full course description  What you'll learn During this course, you will learn how to: Distribute, store, and process data in a cluster Write, configure, and deploy Apache Spark applications Use the Spark interpreters and Spark applications to explore, process, and analyze distributed data Query data using Spark SQL, DataFrames, and Hive tables Deploy a Spark application on the Data Engineering Service What to expect This course is designed for developers and data engineers. All students are expected to have basic Linux experience, and basic proficiency with either Python or Scala programming languages. Basic knowledge of SQL is helpful.  Prior knowledge of Spark and Hadoop is not required. DATE: May 11-14, 2026 9:00 - 17:00 (CEST TIMEZONE) Virtual Classroom, EMEA Read more

This three-day hands-on training course delivers the key concepts and expertise developers need to optimize the performance of their Apache Spark applications. During the course, participants will learn how to identify common sources of poor performance in Spark applications, techniques for avoiding or solving them, and best practices for Spark application monitoring. Optimizing Apache Spark Applications presents the architecture and concepts behind Apache Spark and underlying data platform, then builds on this foundational understanding by teaching students how to tune Spark application code. The course format emphasizes instructor-led demonstrations illustrate both performance issues and the techniques that address them, followed by hands-on exercises that give students an opportunity to practice what they've learned through an interactive notebook environment. Download full course description   This course is designed for software developers, engineers, and data scientists who have experience developing Spark applications and want to learn how to improve the performance of their code. This is not an introduction to Spark. Spark examples and hands-on exercises are presented in Python and the ability to program in this language is required. Basic familiarity with the Linux command line is assumed. Basic knowledge of SQL is helpful.   DATE: April 27-29, 2026 Virtual Classroom, EMEA 9:00 - 17:00 (GMT+2 TIMEZONE) Read more

Welcome to our Introduction Series for Cloudera Education. The following contains excerpts from Admin:230 Administering Cloudera on premises, that is part of our full OnDemand Training Library.  The complete library is available for purchase. Upon completion you will see a path to continue your Cloudera training journey. Many courses include hands-on labs and the OnDemand library comes with 100 hands-on lab hours to practice the concepts and exercises taught. Please enjoy this section of your selected course to help you on your data journey. Disclaimer - The following descriptions and objectives are for the full course. Overview Lab environment is included with this course. Starting in lesson 04 you will be able to launch your environment. This course presents detailed explanation, comprehensive theory, key skills, and recommended practices for successful platform administration. Upon completion of this course a Cloudera Administrator will learn the full range of functionality and capability of Cloudera Manager. This course provides an in-depth explanation and skills to become highly productive with Cloudera Manager and the Cloudera platform. Cloudera Manager is a full featured and mature DevOps tool. It is used to install, configure, operate, troubleshoot, report, and upgrade Cloudera. Many Cloudera Administrators only use a fraction of the capabilities built into Cloudera Manager. This course teaches the architecture, deployment, configuration, logging, reporting, REST API, and much more. The course provides references for architecture and recommended practices used by enterprises around the globe. What to expect While this course is an entry point for aspiring Cloudera Administrators this course is detailed enough for more senior Cloudera Administrators to discover new functionality and capabilities. This course is intended for Linux Administrators who are taking up roles as Platform Administrators. We recommend a minimum of 2 years of system administration experience in industry. Students must have proficiency in Linux. Knowledge of Directory Services, Transport Layer Security, Kerberos, and SQL select statements is helpful. Students must have access to the Internet to reach Amazon Web Services. Read more

Welcome to our Introduction Series for Cloudera Education. The following contains excerpts from DSCI:272 - Predicting with MLOps on Cloudera AI, that is part of our full OnDemand Training Library. The complete library is available for purchase. Upon completion you will see a path to continue your Cloudera training journey. Many courses include hands-on labs and the OnDemand library comes with 100 hands-on lab hours to practice the concepts and exercises taught. Please enjoy this section of your selected course to help you on your data journey. Disclaimer - The following descriptions and objectives are for the full course.   Overview Enterprise data science teams need collaborative access to business data, tools, and computing resources required to develop and deploy machine learning workflows. Cloudera AI, part of the Cloudera platform, provides the solution, giving data science teams the required resources. This course covers machine learning workflows and operations using Cloudera AI. Participants explore, visualize, and analyze data. You will also train, evaluate, and deploy machine learning models. The course walks through an end-to-end data science and machine learning workflow based on realistic scenarios and datasets from a fictitious technology company. The demonstrations and exercises are conducted in Python (with PySpark) using Cloudera AI. ​ Course Length This course includes approximately 8.5 hours of video lectures and demonstrations.  You will need your own environment to work on the labs. The labs will take approximately 7 hours to complete.   What to expect The course is designed for data scientists who need to understand how to utilize Cloudera AI and the Cloudera platform to achieve faster model development and deliver production machine learning at scale. Data engineers, developers, and solution architects who collaborate with data scientists will also find this course valuable. Read more