Big data is hot, and data management and analytics skills are your ticket to a fast-growing, lucrative career. This course will quickly teach you two technologies fundamental to big data: MapReduce and Hadoop. Learn and master the art of framing data analysis problems as MapReduce problems with over 10 hands-on examples. Write, analyze, and run real code along with the instructor– both on your own system, and in the cloud using Amazon's Elastic MapReduce service. By course's end, you'll have a solid grasp of data management concepts.
- Learn the concepts of MapReduce to analyze big sets of data w/ 56 lectures & 5.5 hours of content
- Run MapReduce jobs quickly using Python & MRJob
- Translate complex analysis problems into multi-stage MapReduce jobs
- Scale up to larger data sets using Amazon's Elastic MapReduce service
- Understand how Hadoop distributes MapReduce across computing clusters
- Complete projects to get hands-on experience: analyze social media data, movie ratings & more
- Learn about other Hadoop technologies, like Hive, Pig & Spark
Frank Kane spent 9 years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to hundreds of millions of customers, all the time. Frank holds 17 issued patents in the fields of distributed computing, data mining, and machine learning. In 2012, Frank left to start his own successful company, Sundog Software, which focuses on virtual reality environment technology, and teaching others about big data analysis.
For more details on this course and instructor, click here
. This course is hosted by StackSkills, the premier eLearning destination for discovering top-shelf courses on everything from coding—to business—to fitness, and beyond!