Building Resilient Streaming Analytics Systems on GCP

Start Date: 02/23/2020

Course Type: Common Course

Course Link:

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About Course

*Note: this is a new course with updated content from what you may have seen in the previous version of this Specialization. Processing streaming data is becoming increasingly popular as streaming enables businesses to get real-time metrics on business operations. This course covers how to build streaming data pipelines on Google Cloud Platform. Cloud Pub/Sub is described for handling incoming streaming data. The course also covers how to apply aggregations and transformations to streaming data using Cloud Dataflow, and how to store processed records to BigQuery or Cloud Bigtable for analysis. Learners will get hands-on experience building streaming data pipeline components on Google Cloud Platform using QwikLabs.

Course Syllabus

Cloud Dataflow Streaming Features

Deep Learning Specialization on Coursera

Course Introduction

Building Resilient Streaming Analytics Systems on GCP GCP is a trademark or registered trademark of Google Inc. This course builds on the knowledge and skills that you’ve acquired in previous courses in this specialization. It shows you how to use the GCP cloud computing platform to analyze large streams of data. It covers GCP features, standards, and how to use subscription models to get the most out of your data plan. It covers installation steps for streaming analytics using the Hadoop and Spark frameworks. It also covers setting up nNLP systems in nNLP settings, to reduce latency in your data network. By the end of this course you should be able to: - Use a simple command-line interface to deploy nNLP systems to a Hadoop cluster - Use Hadoop and Spark cores to analyze large streams of data - Set up nNLP systems in your nNLP cluster - Analyze large streams of data with Spark Note: This is an advanced course, and therefore, we assume basic computer science, mathematics, and statistics will be high on your degree requirements.You will need: - A computer with a strong Intel Core i5 or equivalent processor and 8 GB RAM. For benchmarking, we use the Hadoop framework. - At least 1 GB of disk space free. More RAM will speed up your computer. - A web browser with a stable connection. We’ll use a fast internet connection for benchmark

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