Upcoming Sessions
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March
30
ILT - DOPS-244: Apache Kafka on Cloudera - 4794014
Starting:2026/03/30 @ 09:00 AM RiyadhEnding:2026/04/02 @ 05:00 PM Riyadh -
March
31
ILT - ADMIN-335: Administering Data Services on premises - 4899024 - public
Starting:2026/03/31 @ 09:30 AM SingaporeEnding:2026/04/03 @ 05:30 PM Singapore
See All Upcoming Sessions
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 22-24, 2026 9:30 - 17:30 (SGT TIMEZONE) Virtual Classroom, APAC Read more
This course helps customers use Cloudera Data Platform to address data governance tasks, motivated by the need for compliance with regulations such as the European Union's General Data Protection Regulation (GDPR) and the United State's Health Insurance Portability and Accountability Act (HIPAA). What you'll learn Through instructor-led discussion, demonstrations, and hands-on exercises, you will learn how to: Identify which tools in Cloudera Data Platform (CDP) to use for key data governance activities Organize data objects using classifications and business glossary terms Find access history for data objects and policies Use Data Catalog Profilers in CDP to assist in organizing data objects Use Data Catalog to foster collaboration with colleagues View and interpret a data object's lineage Create and apply resource- and tag-based access control policies Create policies for data masking and row-level filtering What to expect This course is best suited for data stewards and others who are responsible for, or have an interest in, implementing regulatory compliance or performing typical data governance activities using the Cloudera Data Platform. Familiarity with basic data governance concepts is helpful, but not required. DATE: April 6-7, 2026 9:00 - 17:00 (GMT+1 TIMEZONE) Virtual Classroom, EMEA Read more
This course introduces Apache Iceberg, a high-performance open table format for organizing petabyte-scale analytic datasets on a file system or object store, available on Cloudera Data Warehouse and Cloudera Data Engineering on both Private and Public Cloud. Combined with Cloudera Data Platform, Iceberg can enable users to build an open data lakehouse architecture for multi-function analytics and to deploy large-scale end-to-end pipelines. This course covers various aspects of Apache Iceberg, such as benefits, architecture, internal operation, read and write operations, and advanced functions, all while drawing comparisons to Hive and building on the students’ existing knowledge and experience. DATE: April 6-9, 2026 9:00 - 17:00 (GMT+1 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
This four-day course teaches the architecture, deployment, and configuration of Cloudera Data Services on Embedded Containerized Services (ECS). Cloudera Data Services provide a state-of-the-art, low- code platform that unifies the entire data lifecycle, reducing development costs and accelerating the development and deployment of use cases. The course starts by covering best practices for managing Docker images and containers. Students will then build a Docker private registry. This Docker private registry will be used to deploy a Data Services cluster on ECS. Students will install, configure, and validate Cloudera Data Engineering, Cloudera Data Warehouse, and Cloudera Machine Learning. Through hands-on exercises, students will gain experience with Kubernetes, install a Private Cloud Embedded Container Service (ECS), and deploy Cloudera Data Services. Additionally, the course covers networking and hardware requirements and explains how Kubernetes pods dynamically scale to support Cloudera Data Services. Who should take this course This immersive course is designed for Cloudera Administrators transitioning to managing Cloudera Data Services on premises. Students should have at least 3 to 5 years of system administration experience. Students must have proficiency in the Linux Command Line Interface and knowledge of Identity Management, including Transport Layer Security and Kerberos. Familiarity with SQL select statements is recommended. Prior experience with Cloudera products is required. Students need reliable internet access to connect to the Amazon Web Services environment used in this course. Recommended prerequisite courses • ADMIN-230: Administering Cloudera on premises • ADMIN-332: Securing Cloudera on premises DATE: April 20-23, 2026 Virtual Classroom, EMEA 9:00 - 17:00 (CEST TIMEZONE) Read more
This four-day instructor-led course begins by introducing Apache Kafka, explaining its key concepts and architecture, and discussing several common use cases. Building on this foundation, you will learn how to plan a Kafka deployment, and then gain hands-on experience by installing and configuring your own cloud-based, multi-node cluster running Kafka on the Cloudera Data Platform (CDP). You will then use this cluster during more than 20 hands-on exercises that follow, covering a range of essential skills, starting with how to create Kafka topics, producers, and consumers, then continuing through progressively more challenging aspects of Kafka operations and development, such as those related to scalability, reliability, and performance problems. Throughout the course, you will learn and use Cloudera’s recommended tools for working with Kafka, including Cloudera Manager, Schema Registry, Streams Messaging Manager, and Cruise Control. DATE: March 30 - April 2, 2026 Virtual Classroom, EMEA 9:00 - 17:00 (GMT+3 TIMEZONE) Read more
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