开始时间: 04/22/2022 持续时间: 10 weeks
所在平台: EdxArchive 课程类别: 其他类别 大学或机构: UC San DiegoX 授课老师: Yoav Freund |
课程主页: https://www.edx.org/archive/big-data-analytics-using-spark-uc-san-diegox-dse230x
课程评论:没有评论
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.
Learn how to analyze large datasets using Jupyter notebooks, MapReduce and Spark as a platform.