Cloudera Educational Services

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: January 18-21, 2027 9:00 - 17:00 (CET TIMEZONE) Virtual Classroom, EMEA Read more

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 four-day 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. Download full course description     DATE: January 19-22, 2027 9:30 - 17:30 (GMT+8 SGT TIMEZONE) Virtual Classroom, APAC Read more

Overview 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 What You'll Learn Students who successfully complete this course will be able to: Understand Apache Spark's architecture, job execution, and how techniques such as lazy execution and pipelining can improve runtime performance Evaluate the performance characteristics of core data structures such as RDD and DataFrames Select the file formats that will provide the best performance for your application Identify and resolve performance problems caused by data skew Use partitioning, bucketing, and join optimizations to improve SparkSQL performance Understand the performance overhead of Python-based RDDs, DataFrames, and user-defined functions Take advantage of caching for better application performance Understand how the Catalyst and Tungsten optimizers work Understand how Workload XM can help troubleshoot and proactively monitor Spark applications performance Learn how the Adaptive Query Execution engine improves performance What to Expect 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: January 4-6, 2027 9:00 - 17:00 (GMT+1 TIMEZONE) Virtual Classroom, EMEA Read more

Cloudera is a fully integrated edge to AI product set. Cloudera Manager is purposely built as the DevOps tooling for building and managing the Cloudera platform. This four-day hands-on 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.   DATE: December 14-17, 2026 9:00 - 17:00 (GMT+1 TIMEZONE) Virtual Classroom, EMEA Read more

This instructor-led course provides hands-on experience with building agentic AI workflows using Cloudera AI. Participants will learn how to work with Cloudera AI Agent Studio, configure large language models, connect tools and MCP servers, build multi-agent workflows, and apply guardrails for secure and reliable AI applications. Through practical use cases, participants will explore how agentic AI can be used to orchestrate tasks, interact with enterprise data and tools, and build intelligent workflows on Cloudera. This course is designed for AI/ML Engineers, Data Scientists, Data Engineers, MLOps Engineers, Solution Architects, Platform Engineers, and other technical professionals who want to build and deploy agentic AI solutions using Cloudera AI.   _________________________________________________ DATE: November 18-19, 2026 9:00 - 17:00 (Madrid TIMEZONE) Onsite Classroom, EMEA Location:  Calle del Mármol, 2, 28005 Madrid Read more

Cloudera is a fully integrated edge to AI product set. Cloudera Manager is purposely built as the DevOps tooling for building and managing the Cloudera platform. This four-day hands-on 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.   DATE: January 11-14, 2027 9:00 - 17:00 (GMT+1 TIMEZONE) Virtual Classroom, EMEA Read more