Covers the principles of the Big Data ecosystem architecture and in-depth understating of selected Big Data technologies that are an important part of such a scalable ecosystem. Important topics covered in this course include Hadoop distributed file system (HDFS), along with the system requirements that drove the need for such distributed file system, MapReduce – a new computing paradigm that enables processing of massive amount of data stored in HDFS, new open-source analytical engines that rely on parallel and in-memory computations to improve the analytical processing time of the massive amount of data, concepts and rigors of machine learning and their implementation using Big Data technologies, functional programming, NoSQL technologies, and integration. The course also covers the implementation and instantiation of a cloud-based Big Data ecosystem that allows illustrating concepts introduced in this class.Offered by Electrical & Comp. Engineering. May not be repeated for credit.
Big Data Technologies
George Mason University
ECE 552 DL1
Electrical & Computer Engineering
Erton Boci (email@example.com)
Times and Days
CS 112 Introduction to Computer Programming or equivalent