Cloudera Educational Services

Overview Apache NiFi 2.0 is revolutionizing data flow automation. This course provides in-depth knowledge of NiFi 2.0's enhanced capabilities, empowering you to build intelligent, efficient, and governed data pipelines for today's most demanding data challenges. You'll explore AI integration, advanced flow management features, and streamlined Python scripting, enabling you to create data solutions that are not only powerful but also adaptable and maintainable. Learn to build more intelligent and efficient NiFi workflows leveraging the new GenAI and Python processors along with the flow governance tools.   What you'll learn During this course, you learn how to:  Integrate Generative AI with Apache NiFi 2.0, including practical use cases.  Understand the key changes in NiFi 2.0 compared to NiFi 1.x, such as deprecated processors and their new replacements.  Clarify the differences between open-source NiFi 2.0 and Cloudera CFM4 with NiFi 2.0, with a focus on Cloudera-specific processors for GenAI.  Perform a migration from NiFi 1.x to NiFi 2.0 and effectively monitor your new NiFi 2.0 instance.  Who Should Take This Course? 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. Prerequisites Participants should have a foundational understanding of data flow concepts and experience with Apache NiFi. Familiarity with Python programming is beneficial but not mandatory.   DATE: February 22, 2027 9:00 - 17:00 (CET TIMEZONE) Virtual Classroom, EMEA Read more

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: February 15-16, 2027 9:00 - 17:00 (CET 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: February 22-25, 2027 9:00 - 17:00 (CET TIMEZONE) Virtual Classroom, EMEA 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: 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