À propos de ce cours
4.5
1,572 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...
Stacks

Cours 2 sur 5 dans la

Spécialisation Data Engineering on Google Cloud Platform
Globe

Cours en ligne à 100 %

Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Calendar

Dates limites flexibles

Réinitialisez les dates limites selon votre disponibilité.
Intermediate Level

Niveau intermédiaire

Clock

Recommandé : 1 week of study, 5-7 hours/week

Approx. 6 heures pour terminer
Comment Dots

English

Sous-titres : English

Compétences que vous acquerrez

Google Cloud DataprocApplication Programming Interfaces (API)Machine Learning
Stacks

Cours 2 sur 5 dans la

Spécialisation Data Engineering on Google Cloud Platform
Globe

Cours en ligne à 100 %

Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Calendar

Dates limites flexibles

Réinitialisez les dates limites selon votre disponibilité.
Intermediate Level

Niveau intermédiaire

Clock

Recommandé : 1 week of study, 5-7 hours/week

Approx. 6 heures pour terminer
Comment Dots

English

Sous-titres : English

Programme du cours : ce que vous apprendrez dans ce cours

1

Section
Clock
2 heures pour terminer

Module 1: Introduction to Cloud Dataproc

...
Reading
16 vidéos (Total 52 min), 2 quiz
Video16 vidéos
Welcome to the Course1 min
Introducing Cloud Dataproc1 min
Defining unstructured data?4 min
Deriving value from unstructured data7 min
Approaches to working with Big Data4 min
MapReduce and Hadoop origins5 min
On prem Hadoop has a lot of overhead1 min
Cloud Dataproc versus Hadoop alternatives2 min
Creating a Dataproc cluster4 min
Dataproc customization3 min
Dataproc and the CLI min
Lab 1: Overview min
Lab 1: Demo and Review7 min
Custom Machine Types3 min
Preemptible VMs3 min
Wrap up min
Quiz1 exercice pour s'entraîner
Module 1 Quiz4 min
Clock
3 heures pour terminer

Module 2: Running Dataproc jobs

...
Reading
13 vidéos (Total 51 min), 3 quiz
Video13 vidéos
Overview of Running Dataproc Jobs2 min
Methods for submitting jobs1 min
Lab 2 Overview1 min
Lab 2: Demo and Review11 min
Separation of Storage and Compute6 min
Evolution of data processing5 min
The importance of networking in data processing3 min
Separating storage and compute with Spark1 min
Submitting Spark jobs3 min
Overview of Spark concepts2 min
Lab Overview min
Lab 3: Demo and Review8 min
Module Wrap Up min
Quiz1 exercice pour s'entraîner
Module 2 Quiz2 min
Clock
3 heures pour terminer

Module 3: Leveraging GCP

...
Reading
10 vidéos (Total 37 min), 3 quiz
Video10 vidéos
Introduction to Leveraging GCP1 min
BigQuery Support8 min
Lab 4: Overview min
Lab 4: Demo and Review4 min
Cluster customization4 min
Installing software on a Dataproc7 min
Lab 5: Overview min
Lab 5: Demo and Review8 min
Wrap up min
Review min
Quiz1 exercice pour s'entraîner
Module 3 Quiz2 min
Clock
1 heure pour terminer

Module 4: Analyzing Unstructured Data

...
Reading
7 vidéos (Total 24 min), 2 quiz
Video7 vidéos
Continuing discussion of Machine Learning1 min
A closer look at Machine Learning3 min
Examples of applied ML3 min
Natural Language Processing close-up2 min
Lab 6: Overview1 min
Lab 6: Demo and Review10 min
Wrap up min
Quiz1 exercice pour s'entraîner
Module 4 Quiz2 min
4.5
Direction Signs

60%

a commencé une nouvelle carrière après avoir terminé ces cours
Briefcase

83%

a bénéficié d'un avantage concret dans sa carrière grâce à ce cours
Money

25%

a obtenu une augmentation de salaire ou une promotion

Meilleurs avis

par CP•Dec 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.

par PG•Aug 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.

Enseignant

Google Cloud Training

À propos de 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....

À propos de la Spécialisation Data Engineering on Google Cloud Platform

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

Foire Aux 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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