The course Big Data Analytics Using Spark is an online class provided by The University of California, San Diego through edX. The skill level of the course is Advanced. It may be possible to receive a verified certification or use the course to prepare for a degree.
Learn how to analyze large datasets using Jupyter notebooks, MapReduce and Spark as a platform.
Course description In data science, data is called “big” if it cannot fit into the memory of a single standard laptop or workstation. The analysis of big datasets requires using a cluster of tens, hundreds or thousands of computers. Effectively using such clusters requires the use of distributed files systems, such as the Hadoop Distributed File System (HDFS) and corresponding computational models, such as Hadoop, MapReduce and Spark. In this course, part of the Data Science MicroMasters program, you will learn what the bottlenecks are in massive parallel computation and how to use spark to minimize these bottlenecks. You will learn how to perform supervised an unsupervised machine learning on massive datasets using the Machine Learning Library (MLlib). In this course, as in the other ones in this MicroMasters program, you will gain hands-on experience using PySpark within the Jupyter notebooks environment.
To obtain a verified certificate from edX / The University of California, San Diego you have to finish this course or the latest version of it, if there is a new edition. The class may be free of charge, but there could be some cost to receive a verified certificate (350.00 USD) or to access the learning materials. The specifics of the course may have been changed, please consult the provider to get the latest quotes and news.
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