About this Course

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Intermediate Level
Approx. 13 hours to complete
English
Subtitles: English, Spanish
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 13 hours to complete
English
Subtitles: English, Spanish

Instructor

Offered by

Google Cloud logo

Google Cloud

Syllabus - What you will learn from this course

Week
1

Week 1

6 minutes to complete

Introduction

6 minutes to complete
2 videos (Total 6 min)
2 videos
Getting Started with Google Cloud and Qwiklabs4m
1 hour to complete

Introduction to Batch Data Pipelines

1 hour to complete
5 videos (Total 18 min)
5 videos
Quality considerations1m
How to carry out operations in BigQuery3m
Shortcomings3m
ETL to solve data quality issues4m
1 practice exercise
EL, ELT, ETL30m
2 hours to complete

Executing Spark on Cloud Dataproc

2 hours to complete
9 videos (Total 49 min)
9 videos
Running Hadoop on Cloud Dataproc10m
GCS instead of HDFS6m
Optimizing Dataproc5m
Optimizing Dataproc Storage9m
Optimizing Dataproc Templates and Autoscaling4m
Optimizing Dataproc Monitoring3m
Lab Intro: Running Apache Spark jobs on Cloud Dataproc27s
Summary31s
1 practice exercise
Executing Spark on Cloud Dataproc4m
Week
2

Week 2

3 hours to complete

Manage Data Pipelines with Cloud Data Fusion and Cloud Composer

3 hours to complete
11 videos (Total 45 min)
11 videos
Components of Data Fusion2m
Building a Pipeline6m
Exploring Data using Wrangler1m
Lab: Building and executing a pipeline graph in Cloud Data Fusion17s
Orchestrating work between GCP services with Cloud Composer1m
Apache Airflow Environment1m
DAGs and Operators12m
Workflow scheduling6m
Monitoring and Logging4m
Lab: An Introduction to Cloud Composer12s
1 practice exercise
Cloud Data Fusion and Cloud Composer30m
7 hours to complete

Serverless Data Processing with Cloud Dataflow

7 hours to complete
12 videos (Total 40 min)
12 videos
Why customers value Dataflow3m
Building Cloud Dataflow Pipelines in code3m
Key considerations with designing pipelines2m
Transforming data with PTransforms3m
Lab: Building a Simple Dataflow Pipeline17s
Aggregating with GroupByKey and Combine7m
Lab: MapReduce in Cloud Dataflow18s
Side Inputs and Windows of data4m
Lab: Practicing Pipeline Side Inputs11s
Creating and re-using Pipeline Templates3m
Cloud Dataflow SQL pipelines3m
1 practice exercise
Data Processing with Cloud Dataflow30m
4 minutes to complete

Summary

4 minutes to complete
1 video (Total 4 min)
1 video

Reviews

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Frequently Asked Questions

  • Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.

  • If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.

  • Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.

  • If you complete the course successfully, your electronic Course Certificate will be added to your Accomplishments page - from there, you can print your Course Certificate or add it to your LinkedIn profile.

  • This course is one of a few offered on Coursera that are currently available only to learners who have paid or received financial aid, when available.

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

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