Cloudera Educational Services

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: October 27-30, 2025 Virtual Classroom, AMER 9:00 - 17:00 (US East TIMEZONE) 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: October 27-30, 2025 Virtual Classroom, AMER 9:00 - 17:00 (Central TIMEZONE) Read more

DESCRIPTION DATE: November 17-20, 2025 Virtual Classroom, AMER 9:00 - 17:00 (Central TIMEZONE) Read more

Welcome to our Introduction Series for Cloudera Education. The following contains excerpts from Admin:230 Administering Cloudera on premises, that is part of our full OnDemand Training Library.  The complete library is available for purchase. Upon completion you will see a path to continue your Cloudera training journey. Many courses include hands-on labs and the OnDemand library comes with 100 hands-on lab hours to practice the concepts and exercises taught. Please enjoy this section of your selected course to help you on your data journey. Disclaimer - The following descriptions and objectives are for the full course. Overview Lab environment is included with this course. Starting in lesson 04 you will be able to launch your environment. This 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. This course provides an in-depth explanation and skills to become highly productive with Cloudera Manager and the Cloudera platform. Cloudera Manager is a full featured and mature DevOps tool. It is used to install, configure, operate, troubleshoot, report, and upgrade Cloudera. Many Cloudera Administrators only use a fraction of the capabilities built into Cloudera Manager. This course teaches the architecture, deployment, configuration, logging, reporting, REST API, and much more. The course provides references for architecture and recommended practices used by enterprises around the globe. What to expect While this course is an entry point for aspiring Cloudera Administrators this course is detailed enough for more senior Cloudera Administrators to discover new functionality and capabilities. This course is intended for Linux Administrators who are taking up roles as Platform Administrators. We recommend a minimum of 2 years of system administration experience in industry. Students must have proficiency in Linux. Knowledge of Directory Services, Transport Layer Security, Kerberos, and SQL select statements is helpful. Students must have access to the Internet to reach Amazon Web Services. Read more

Welcome to our Introduction Series for Cloudera Education. The following contains excerpts from DSCI:272 - Predicting with MLOps on Cloudera AI, that is part of our full OnDemand Training Library. The complete library is available for purchase. Upon completion you will see a path to continue your Cloudera training journey. Many courses include hands-on labs and the OnDemand library comes with 100 hands-on lab hours to practice the concepts and exercises taught. Please enjoy this section of your selected course to help you on your data journey. Disclaimer - The following descriptions and objectives are for the full course.   Overview 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 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. ​ Course Length This course includes approximately 8.5 hours of video lectures and demonstrations.  You will need your own environment to work on the labs. The labs will take approximately 7 hours to complete.   What to expect The course is designed for data scientists who need to understand how to utilize Cloudera AI and the Cloudera platform to achieve faster model development and deliver production machine learning at scale. Data engineers, developers, and solution architects who collaborate with data scientists will also find this course valuable. 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: September 23-26, 2025 Virtual Classroom, EMEA 9:00 - 17:00 (CET TIMEZONE) Read more