University of California, San Diego is offering a free online course on Big Data Analytics Using Spark. In data science, data is called “big” if it cannot fit into the memory of a single standard laptop or workstation.
In this ten-week course, applicants will learn how to analyze large data sets using Jupiter notebooks, Map Reduce and Spark as a platform. This course will start on April 1, 2018.
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Course At A Glance
Length: 10 weeks
Effort: 10 hours pw
Subject: Data Analysis & Statistics
Institution: University of California, San Diego and edx
Certificate Available: Yes, Add a Verified Certificate for $350
Session: Course Starts on December 31, 2019
The University of California, San Diego (UC San Diego) is a student-centred, research-focused, service-oriented public institution that provides an opportunity for all. This young university has made its mark regionally, nationally and internationally.
About This 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, Map Reduce and Spark.
Why Take This Course?
You will learn how to perform supervised 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.
- 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
Dr. Freund is a Professor of Computer Science and Engineering at the University of California San Diego.
The previous courses in the Micro Masters program: DSE200x, DSE210x and DSE220x
How To Join This Course
- Go to the course website link
- Create an edX account to SignUp
- Choose “Register Now” to get started.
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