Cloudera Educational Services

This two-day instructor-led training course teaches students the development and operations skills needed to support Cloudera Streaming Analytics, a framework for low-latency processing and analytics powered by Apache Flink and Cloudera's innovative SQL Stream Builder. Through extensive hands-on exercises, students will gain experience deploying and managing a Flink cluster, developing and running Flink applications, and using SQL Stream Builder's continuous SQL to perform analytics on streaming data. DATE: April 26-27, 2027 9:00 - 17:00 (CET 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: April 26-29, 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: April 19-22, 2027 9:00 - 17:00 (CET TIMEZONE) Virtual Classroom, EMEA 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: April 19-22, 2027 9:00 - 17:00 (CET TIMEZONE) Virtual Classroom, EMEA Read more

Apache Ozone is the next-generation hybrid storage service offering versatility and out-of-the-box compatibility. Ozone is an object storage format exceeding the limitations of HDFS. This course teaches architecture, internal operations, installation, file system usage, best practices, security, maintenance, monitoring, tuning and testing. Download full course description  What you'll learn This course teaches the Ozone internal architecture and how to install, use, maintain, monitor, tune, integrate, and test the the Ozone service in a secure environment. Participants will gain the following skills: Understanding the Benefits of Using Ozone Installing and Configuring Secure Ozone Managing Files and Objects in Ozone Performance Tuning and Doing Baseline Tests Controlling Replication and Understanding Failover and Recovery Performing Maintenance Tasks  Monitoring Ozone Using Recon Service Integrating Hive, Impala, Spark, Nifi, and Flink with Ozone Migrating Data from HDFS to Ozone What to expect This advanced course is for administrators who are currently using CDP Private Cloud Base. The course will appeal to technicians, such as data engineers and applications developers, who are migrating data and applications to Apache Ozone. Prior experience of Cloudera Data Platform, to include HDFS, YARN, and Hive, is expected. Students must have access to the Internet to reach the classroom environments, which are located on Amazon Web Services.   DATE: April 12-15, 2027 9:00 - 17:00 (CET TIMEZONE) Virtual Classroom, EMEA Read more

This four-day Analyzing with Data Warehouse course will teach you to apply traditional data analytics and business intelligence skills to big data. This course presents the tools data professionals need to access, manipulate, transform, and analyze complex data sets using SQL and familiar scripting languages. Download full course description What you'll learn Through instructor-led discussion and interactive, hands-on exercises, participants will navigate the ecosystem, learning how to: Use Apache Hive and Apache Impala to access data through queries Identify distinctions between Hive and Impala, such as differences in syntax, data formats, and supported features Write and execute queries that use functions, aggregate functions, and subqueries Use joins and unions to combine datasets Create, modify, and delete tables, views, and databases Load data into tables and store query results Select file formats and develop partitioning schemes for better performance Use analytic and windowing functions to gain insight into their data Store and query complex or nested data structures Process and analyze semi-structured and unstructured data Optimize and extend the capabilities of Hive and Impala Determine whether Hive, Impala, an RDBMS, or a mix of these is the best choice for a given task Utilize the benefits of CDP Public Cloud Data Warehouse   What to expect This course is designed for data analysts, business intelligence specialists, developers, system architects, and database administrators. Some knowledge of SQL is assumed, as is basic Linux command-line familiarity.     DATE: April 5-8, 2027 9:00 - 17:00 (CET TIMEZONE) Virtual Classroom, EMEA Read more