Big Data Analytics Using Spark

MOOC
Big Data Analytics Using Spark
Language
English
Duration
3 months
Certificate
Certification paid
Course by EdX
Big Data Analytics Using Spark
What will you learn?
Programming Spark using Pyspark
Identifying the computational tradeoffs in a Spark application
Performing data loading and cleaning using Spark and Parquet
Modeling data through statistical and machine learning methods
About the course

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.

Program
Big Data Analytics Using Spark
Learn how to analyze large datasets using Jupyter notebooks, MapReduce and Spark as a platform.
Big Data Analytics Using Spark
Learn how to analyze large datasets using Jupyter notebooks, MapReduce and Spark as a platform.
Big Data Analytics Using Spark
Learn how to analyze large datasets using Jupyter notebooks, MapReduce and Spark as a platform.
Lecturers
Yoav Freund
Yoav Freund
Professor of Computer Science and Engineering UC San Diego
Platform
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