Thomas Henson is a known Data Engineering Advocate who is known for helping teams solve complex problems with Big Data. Thomas is a Software Engineer at heart and Big Data Analytics Evangelist by trade; where he specializes in solving real world problems with Scaled-out Computing Solutions (Hadoop, Spark, Flink, Redshift, Kafka, etc.). He is proud Alumni of the University of North Alabama; where he received both his undergraduate and graduate degree. Thomas has been seen at many conferences events like Hadoop Summit, Future of Data Roadshow and Fed Forum. You can always check him out at thomashenson.com or on twitter at @henson_tm.
Data Engineering Courses
Pig Latin: Getting Started – Course designed to get developers familiar with the Pig Latin language fundamentals. Learn how to write your first MapReduce job without Java.
Getting Started with HDFS – Learning to work with Hadoop Distributed File System (HDFS) is a baseline skill for anyone administering or developing in the Hadoop ecosystem. In this course, you will learn how to work with HDFS, Hive, Pig, Sqoop and HBase from the command line.
Analyzing Machine Data with Splunk – Splunk is one of the most used applications for analyzing unstructured data in the data center. This course will teach you the basics of setting up Splunk, writing Splunk queries, and running Splunk with Hadoop.
Getting Started with Hortonworks Data Platform – Hortonworks Data Platform is one of the leading Hadoop distributed platform. In this course learn how to build and deploy a HDP cluster in your environment.
Enteprise Skills in Hortonworks Data Platform – Data Engineers are in high demand mostly because Enterprises are adopting Hadoop at hyperscale. In my newest Pluralsight course I cover those skills Data Engineers must have to be successful in the Enterprise.
Implementing Neural Networks with TFLearn – Tensorflow course taking a Data Engineers approach to learning how to get started in Deep Learning. In this course we walk through how to writing layers using Tensorflow Python APIs. This course is targeted at those just getting started with Machine Learning.