Cloudera Educational Services

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 8:00 - 14:00 (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

One of the most critical functions of a data-driven enterprise is the ability to manage ingest and data flow across complex ecosystems.  Does your team have the tools and skill sets to succeed at this? Apache NiFi and this four-day course provides the fundamental concepts and experience necessary to automate the ingress, flow, transformation, and egress of data using NiFi. The course also covers tuning, troubleshooting, and monitoring the dataflow process as well as how to integrate a dataflow within the Cloudera CDP Hybrid ecosystem and external systems. Download full course description  What you'll learn During this course, you learn how to:  Define, configure, organize, and manage dataflows  Transform and trace data as it flows to its destination  Track changes to dataflows with NiFi Registry  Use the NiFi Expression Language to control dataflows  Optimize dataflows for better performance and maintainability Connect dataflows with other systems, such as Apache Kafka, Apache Hive, and HDFS Utilize the Data Flow Service What to expect This course is designed for developers, data engineers, administrators, and others with an interest in learning NiFi’s innovative no-code, graphical approach to data ingest. Although programming experience is not required, basic experience with Linux is presumed, and previous exposure to big data concepts and applications is helpful. DATE: March 1-4, 2027 9:00 - 17:00 (GMT+1 TIMEZONE) Virtual Classroom, EMEA Read more

This 3-day course by Cloudera Education introduces participants to implementing enterprise data governance and lineage using Cloudera Data Governance and Cloudera Data Lineage. Learners will gain practical knowledge of how to manage, control, classify, and trace data across the enterprise while supporting regulatory and compliance requirements such as GDPR and HIPAA. The course covers key governance concepts including data classification, metadata management, data protection, lineage tracking, impact analysis, and policy enforcement to improve data transparency, regulatory compliance, and overall trust in enterprise data ecosystems.   DATE: November 30-December 2, 2026 9:00 - 17:00 (GMT-6:00 CST TIMEZONE) Virtual Classroom, AMER   Read more