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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. December 12th - 13th, 2022 Virtual Classroom, EMEA 9:00 - 17:00 (CET) Read More

Note: Enrolling here will not give you access to the actual course. The course is available by purchasing the Full OnDemand Library subscription.  About This Course Cloudera's Introduction to Apache Kudu course teaches students the basics of Apache Kudu, a data storage system for the Hadoop platform that is optimized for both analytical queries and the ability to read and write individual records. The course covers common Kudu use cases and Kudu architecture. Students will learn how to create, manage, and query Kudu tables using Impala, and to develop Spark applications that use data stored in Kudu. Course Length This module includes 1 hour of video content. Hands-on exercises will take approximately 3 hours. Subscribers to the Cloudera OnDemand Full Library are given 100 hours of lab time to use across all courses. Audience and Prerequisites This material is intended for a broad audience of students involved with either software development or data analysis. This would include software developers, data engineers, DBAs, data scientists, and data analysts. Students should know SQL. Familiarity with Impala is preferred but not required. Students should also know how to develop Apache Spark applications using either Python or Scala. Basic Linux experience is expected. Note: Enrolling here will not give you access to the actual course. The course is available by purchasing the Full OnDemand Library subscription.  Read More

About This Module This module introduces data engineers and data analysts to the Cloudera Data Warehouse (CDW) service. It introduces basic concepts, and then provides a choice to continue with a Data Engineer track, which shows how to create and tune important entities within CDW, or with a Data Analyst track, which shows how to access tables and views using different interface methods. Module Length This module includes 52 minutes of video content. The videos for the Data Analyst track add to 38 minutes; the videos for the Engineer track add to 33 minutes. Note: In order to complete the hands-on exercises for this course, students must have access to CDW through their organization. Audience and Prerequisites This module is designed for data analysts and data engineers. There are no prerequisites, though access to a working Cloudera Data Platform with CDW is required in order to complete the hands-on exercises. Grading for This Module There are seven chapters in this module, but you only need to complete four quizzes with 75% or better to pass. (One chapter does not include a quiz.)  After the first three chapters, you can choose the two Data Engineer track chapters, or the two Data Analyst track chapters. Your reported grade will include the quizzes for chapters you did not take, but the overall passing level has been lowered to 50%. This means you do not need to take the quizzes for the other track. However, you are welcome to complete all seven modules (and take all six quizzes).  Read More

About This Module This module introduces the Cloudera Machine Learning (CML) experience on CDP. Module Length This module includes one hour of video content. Audience and Prerequisites This course is ideal for anyone who wants to understand the capabilities of the Cloudera Machine Learning experience and how to navigate in the CML workbench interface. A Note about This Free Course This course is a free introduction to CML.  The regular (paid) version of this course is Cloudera Machine Learning Training. The course begins with these same five chapters, but it continues to provide much more in-depth training, using either Python or R. If you're interested in learning more, please take a look at that course in our store! (Note that the regular course is available only through the Full OnDemand Library subscription.) Read More

About This Course Whether you’re building big data applications, developing data pipelines, or working on machine learning projects, it’s essential to manage changes to your code. Although developers and data scientists have employed a variety of tools for this over the years, an open source version control system called git has emerged as the standard tool for thousands of organizations around the world. This course introduces students to the Git version control system through a series of lectures, demonstrations, and exercises. Course Length This module includes over an hour of video content. The hands-on exercises for this free course  requires your own environment. They may take up to 3 hours. If you have a paid subscription you should enroll in Just Enough Git which includes an environment. Audience and Prerequisites This course is best suited to developers and data scientists who feel comfortable performing basic operations from the Linux command line. No prior experience with git or other revision control systems is necessary. Read More

Note: Enrolling here will not give you access to the actual course. The course is available by purchasing the Full OnDemand Library subscription.  About This Course Whether you’re building big data applications, developing data pipelines, or working on machine learning projects, it’s essential to manage changes to your code. Although developers and data scientists have employed a variety of tools for this over the years, an open source version control system called git has emerged as the standard tool for thousands of organizations around the world. This course introduces students to the Git version control system through a series of lectures, demonstrations, and hands-on exercises. Course Length This module includes over an hour of video content. Hands-on exercises may take an additional 3 hours.  Audience and Prerequisites This course is best suited to developers and data scientists who feel comfortable performing basic operations from the Linux command line. No prior experience with git or other revision control systems is necessary. Note: Enrolling here will not give you access to the actual course. The course is available by purchasing the Full OnDemand Library subscription.  Read More

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