About this Course
4.5
1,589 ratings
209 reviews
This 1-week, accelerated course builds upon previous courses in the Data Engineering on Google Cloud Platform specialization. Through a combination of video lectures, demonstrations, and hands-on labs, you'll learn how to create and manage computing clusters to run Hadoop, Spark, Pig and/or Hive jobs on Google Cloud Platform. You will also learn how to access various cloud storage options from their compute clusters and integrate Google’s machine learning capabilities into their analytics programs. In the hands-on labs, you will create and manage Dataproc Clusters using the Web Console and the CLI, and use cluster to run Spark and Pig jobs. You will then create iPython notebooks that integrate with BigQuery and storage and utilize Spark. Finally, you integrate the machine learning APIs into your data analysis. Pre-requisites • Google Cloud Platform Big Data & Machine Learning Fundamentals (or equivalent experience) • Some knowledge of Python...
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100% online courses

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Calendar

Flexible deadlines

Reset deadlines in accordance to your schedule.
Intermediate Level

Intermediate Level

Clock

Approx. 6 hours to complete

Suggested: 1 week of study, 5-7 hours/week...
Comment Dots

English

Subtitles: English...

Skills you will gain

Google Cloud DataprocApplication Programming Interfaces (API)Machine Learning
Globe

100% online courses

Start instantly and learn at your own schedule.
Calendar

Flexible deadlines

Reset deadlines in accordance to your schedule.
Intermediate Level

Intermediate Level

Clock

Approx. 6 hours to complete

Suggested: 1 week of study, 5-7 hours/week...
Comment Dots

English

Subtitles: English...

Syllabus - What you will learn from this course

Week
1
Clock
2 hours to complete

Module 1: Introduction to Cloud Dataproc

...
Reading
16 videos (Total 52 min), 2 quizzes
Video16 videos
Introducing Cloud Dataproc1m
Defining unstructured data?4m
Deriving value from unstructured data7m
Approaches to working with Big Data4m
MapReduce and Hadoop origins5m
On prem Hadoop has a lot of overhead1m
Cloud Dataproc versus Hadoop alternatives2m
Creating a Dataproc cluster4m
Dataproc customization3m
Dataproc and the CLIm
Lab 1: Overviewm
Lab 1: Demo and Review7m
Custom Machine Types3m
Preemptible VMs3m
Wrap upm
Quiz1 practice exercise
Module 1 Quiz4m
Clock
3 hours to complete

Module 2: Running Dataproc jobs

...
Reading
13 videos (Total 51 min), 3 quizzes
Video13 videos
Methods for submitting jobs1m
Lab 2 Overview1m
Lab 2: Demo and Review11m
Separation of Storage and Compute6m
Evolution of data processing5m
The importance of networking in data processing3m
Separating storage and compute with Spark1m
Submitting Spark jobs3m
Overview of Spark concepts2m
Lab Overviewm
Lab 3: Demo and Review8m
Module Wrap Upm
Quiz1 practice exercise
Module 2 Quiz2m
Clock
3 hours to complete

Module 3: Leveraging GCP

...
Reading
10 videos (Total 37 min), 3 quizzes
Video10 videos
BigQuery Support8m
Lab 4: Overviewm
Lab 4: Demo and Review4m
Cluster customization4m
Installing software on a Dataproc7m
Lab 5: Overviewm
Lab 5: Demo and Review8m
Wrap upm
Reviewm
Quiz1 practice exercise
Module 3 Quiz2m
Clock
1 hour to complete

Module 4: Analyzing Unstructured Data

...
Reading
7 videos (Total 24 min), 2 quizzes
Video7 videos
A closer look at Machine Learning3m
Examples of applied ML3m
Natural Language Processing close-up2m
Lab 6: Overview1m
Lab 6: Demo and Review10m
Wrap upm
Quiz1 practice exercise
Module 4 Quiz2m
4.5
Direction Signs

60%

started a new career after completing these courses
Briefcase

83%

got a tangible career benefit from this course
Money

25%

got a pay increase or promotion

Top Reviews

By CPDec 29th 2017

Really enjoyed it, woudl have liked to spend more time with the APIs and integrate with real time web downloads. There are a few bugs and misprints, but wasn't too hard to find them.

By PGAug 8th 2018

The course was really helpful to understand how to use google bigdata offering - dataproc for creating and managing Hadoop/hive/spark/pig and many more opensource bigdata products.

About Google Cloud

We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success....

About the Data Engineering on Google Cloud Platform Specialization

>>> By enrolling in this specialization you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<< This five-week, accelerated online specialization provides participants a hands-on introduction to designing and building data processing systems on Google Cloud Platform. Through a combination of presentations, demos, and hand-on labs, participants will learn how to design data processing systems, build end-to-end data pipelines, analyze data and carry out machine learning. The course covers structured, unstructured, and streaming data. This course teaches the following skills: • Design and build data processing systems on Google Cloud Platform • Leverage unstructured data using Spark and ML APIs on Cloud Dataproc • Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow • Derive business insights from extremely large datasets using Google BigQuery • Train, evaluate and predict using machine learning models using Tensorflow and Cloud ML • Enable instant insights from streaming data This class is intended for developers who are responsible for: • Extracting, Loading, Transforming, cleaning, and validating data • Designing pipelines and architectures for data processing • Creating and maintaining machine learning and statistical models • Querying datasets, visualizing query results and creating reports...
Data Engineering on Google Cloud Platform

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. If you’d like to take this course, but can’t afford the course fee, we encourage you to submit a financial aid application.

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