Cloudera Educational Services

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: February 1-4, 2026 9:00 - 17:00 (CET TIMEZONE) Virtual Classroom, EMEA Read more

Designing Edge to AI Applications is a 4-day learning event that addresses advanced big data architecture topics for building edge to AI applications to cover streaming, operational data processing, analytics, and machine learning.  The workshop brings together technical contributors into a group setting to design and architect solutions to a challenging business problem. The workshop addresses big data architecture problems in general, and then applies them to the design of a challenging system. Throughout the highly interactive workshop, participants apply concepts to real-world examples resulting in detailed synergistic discussions. The workshop is conducive for participants to learn techniques for architecting big data systems, not only from Cloudera’s experience but also from the experiences of fellow participants.  More specifically, this workshop addresses advanced big data architecture topics, including, data formats, transformation, transactions, real-time, batch and machine learning processing, scalability, fault tolerance, security, and privacy, minimizing the risk of an unsound architecture and technology selection. What you'll learn Cloudera Data Platform Big Data Architecture Building Scalable applications Building Fault Tolerant Solutions Security and Privacy Deployment on Public, Private, and Hybrid Cloud What to expect Participants should mainly be architects, developer team leads, big data developers, data engineers, senior analysts, dev ops admins and machine learning developers who are working on big data or streaming applications and have an interest in how to design and develop such applications on CDP. To gain the most from the workshop, participants should have working knowledge of popular Big Data and streaming technologies such as HDFS, Spark, Kafka, Hive/Impala, Data Formats, and relational database management systems. Detailed API level knowledge is not needed, as there will not be any programming activities and instead the focus will be on architecture design. The workshop will be divided into small groups to discuss the problems, develop solutions, and present their solutions. DATE: February 8-11, 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: February 8-11, 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: February 1-4, 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: January 25-28, 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: January 18-21, 2027 9:00 - 17:00 (CET TIMEZONE) Virtual Classroom, EMEA Read more