Cloudera is offering several training courses for Apache Hadoop over the dates surrounding Hadoop Summit. There are five different courses in all spanning the dates of June 27th to July 1st. Three of these courses are specifically designed to provide the necessary knowledge for a robust overall understanding of Hadoop and they tackle the elephant from several perspectives — developer, system administrator, and managerial. The other two training sessions focus on projects within the Hadoop ecosystem; namely Hive, Pig, and HBase.
Cloudera Developer Bootcamp for Apache Hadoop is a two-day course designed for developers who wish to learn the MapReduce framework and how to write programs against its API. The course covers similar material to our standard three-day Developer training, but has been condensed into two intensive days with extended course hours. At the end of the course, attendees have the opportunity to take an exam which, if passed, confers the Cloudera Certified Hadoop Developer credential.
Cloudera Administrator Training for Apache Hadoop is a two-day course designed for system administrators. It teaches Hadoop system recommendations, installation, configuration, troubleshooting, and best practices. At the end of the course, attendees have the opportunity to take the Cloudera Certified Hadoop Administrator exam.
Clouderas Manager Training for Apache Hadoop is a one-day course focused on providing decision makers the answers to questions like: When is Hadoop appropriate? What are people using Hadoop for? How does Hadoop fit into our existing environment? And many more.
Cloudera Training for Apache Hive and Pig is a two-day, hands-on course for people who want to manipulate and query large amounts of data without needing to write complex Java MapReduce code. Hive provides a language very similar to SQL, while Pig is an easy-to-learn but sophisticated scripting language. No Java programming knowledge is required for this course.
Cloudera Developer Training for Apache HBase is also a hands-on course that will provide you with all the information necessary for using HBase as a distributed data store to achieve low-latency queries and highly scalable throughput.