Organizations need skilled, forward-thinking Big Data practitioners who can apply their business and technical skills to unstructured data such as tweets, posts, pictures, audio files, videos, sensor data, and satellite imagery and more to identify behaviors and preferences of prospects, clients, competitors, and others.
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About this Course
Computer and IT literacy.
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Try Coursera for BusinessWhat you will learn
Explain how streaming data and Spark Structured Streaming empower machine learning and AI tasks.
Define graph theory, describe Apache Spark GraphFrames, and identify data suitable for GraphFrames.
Describe how ETL processes work with Apache Spark and machine learning and extend that knowledge to Spark MLlib capabilities and related benefits.
Explain supervised learning, unsupervised learning, and clustering, and explain how to use the k-means clustering algorithm with Spark MLlib.
Computer and IT literacy.
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessOffered by
Syllabus - What you will learn from this course
Spark for Data Engineering
SparkML
Final Project
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- 2 stars7.59%
- 1 star13.92%
TOP REVIEWS FROM DATA ENGINEERING AND MACHINE LEARNING USING SPARK
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