Training and Events
Introduction to Hadoop - London - 2-Day Training Course
|Mind Project Ltd|
Simon Walkowiak MBPsS
16/10/2017 - 17/10/2017
CAP House, 1st Floor, 9-12 Long Lane, London, EC1A 9HA
View in Google Maps (EC1A 9HA)
Mind Project Ltd
1. Course description.
This two-day training course explores major characteristics and functionalities of Apache Hadoop platform and its ecosystem of tools for Big Data processing and analysis. The course provides a first-hand practical experience in Hadoop Distributed File System (HDFS) and MapReduce frameworks by the means of a number of presentations and tutorials during which the attendees will learn how to design and perform simple MapReduce programs to process the data and calculate a set of statistics. The course can also serve as a gentle introduction to the basics of Java programming language and essential Hadoop File System shell commands. During the course you will learn to:
During the course the attendees will perform several simple MapReduce jobs on a Linux-based Mind Project Hadoop cluster.
The course will run for two days from 9:30am until ~5:00pm on each day and will consist of alternating lecture-style presentations and practical tutorials. The example datasets used during tutorial sessions will come from social sciences, economics and business fields, however the contents may vary depending on specific interests of participants (based on the Participant's Skills Inventory). There will be two 15-minute coffee/tea breaks and one 1-hour lunch break on each day.
3. What is included?
Apart from the contents of the course, Mind Project will provide the participants with the following:
4. Further instructions.
Should you have any questions please contact Mind Project Ltd at email@example.com or by phone on 0203 322 3786. Please visit the course website at https://www.mindproject.io/product/introduction-to-hadoop-london-october-2017/.
Entry (no or almost no prior knowledge)
£450 per person for the whole course (regular fee).
Website and registration
Quantitative Software, Technology, ICT and Software (other), Big Data , HDFS , distributed file system , Hive , HBase , Cassandra , Java language , distributed computing , cloud computing , parallel computing , Hadoop , Spark , MapReduce
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