This 1-week accelerated on-demand course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities.
At the end of this course, participants will be able to:
• Identify the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform
• Use CloudSQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform
• Employ BigQuery and Cloud Datalab to carry out interactive data analysis
• Choose between Cloud SQL, BigTable and Datastore
• Train and use a neural network using TensorFlow
• Choose between different data processing products on the Google Cloud Platform
Before enrolling in this course, participants should have roughly one (1) year of experience with one or more of the following:
• A common query language such as SQL
• Extract, transform, load activities
• Data modeling
• Machine learning and/or statistics
• Programming in Python
Google Account Notes:
• Google services are currently unavailable in China.
Looking for the English version of this course? Check out https://www.coursera.org/learn/gcp-big-data-ml-fundamentals/
このコースの日本語版をお探しですか？https://www.coursera.org/learn/gcp-big-data-ml-fundamentals-jp/
Этот курс входит в специализацию ''Специализация Data Engineering on Google Cloud Platform'
Google Cloud Platform Big Data and Machine Learning Fundamentals
от партнера
Об этом курсе
4.6
Оценки: 4,536
Приобретаемые навыки
TensorflowBigqueryGoogle Cloud PlatformCloud Computing
Программа курса: что вы изучите
Неделя
1Introduction to the Data and Machine Learning on Google Cloud Platform Specialization
4 видео ((всего 13 мин.)), 1 материал для самостоятельного изучения
4 видео
Course Overview and Agenda5мин
Getting Started with Google Cloud Platform and Qwiklabs2мин
Meet Your Instructor3мин
1 материал для самостоятельного изучения
Please read me1мин
Introduction to Google Cloud Platform and its Big Data Products
In this module you will be introduced to Google Cloud Platform and the data handling aspects of the platform.
5 видео ((всего 31 мин.)), 1 тест
5 видео
What is the Google Cloud Platform?14мин
GCP Big Data Products9мин
Usage Scenarios5мин
Module Resources27
1 практическое упражнение
Module Review2мин
Foundations of GCP Compute and Storage
In this module, we introduce the foundations of the Google Cloud Platform: compute and storage and introduce how they work to provide data ingest, storage, and federated analysis.
9 видео ((всего 54 мин.)), 1 материал для самостоятельного изучения, 3 тестов
9 видео
CPUs On Demand7мин
Lab Overview37
Lab Review8мин
A Global Filesystem14мин
Lab Overview1мин
Lab Review14мин
Module Review3мин
Module Resources3мин
1 материал для самостоятельного изучения
Module Resources10мин
1 практическое упражнение
Module Review4мин
Data Analysis on the Cloud
In this module we introduce the common Big Data use cases that Google will manage for you. These are the things that are widely done in industry today and for which we provide easy migration to the cloud.
10 видео ((всего 90 мин.)), 3 тестов
10 видео
Stepping Stones to Transformation20мин
Your SQL Database in the Cloud5мин
Lab Overview24
Lab Review22мин
Managed Hadoop in the Cloud8мин
Lab Overview17
Lab Review27мин
Module Review3мин
Module Resources1мин
1 практическое упражнение
Module Review4мин
Scaling Data Analysis and Machine Learning
This module is about the more transformational technologies in Google Cloud platform that may not have immediate parallels to technologies that attendees are using (“what's next”).
21 видео ((всего 82 мин.)), 1 материал для самостоятельного изучения, 4 тестов
21 видео
Fast Random Access11мин
Warehouse and Interactively Query Petabytes with Google BigQuery3мин
Ingesting data into BigQuery2мин
Interactive, Iterative Development with Cloud Datalab1мин
Cloud Datalab : Demo3мин
Datalab supports BigQuery2мин
Lab Overview27
Lab Review : Setting up Datalab5мин
Lab Review : Working in ipython notebook6мин
Introduction25
Machine Learning with TensorFlow8мин
Training and creating a Neural Network Model : Part 11мин
Training and Creating a Neural Network Model : Part 25мин
Lab Overview4мин
Pre-built Machine Learning Models4мин
Pre-built ML APIs : Examples8мин
Lab Review8мин
Module Review2мин
Scaling Data Analysis : Resources10
Machine Learning : Resources14
1 материал для самостоятельного изучения
Scaling Data Analysis : Resources1мин
1 практическое упражнение
Module Review18мин
Data Processing Architectures: Scalable Ingest, Transform and Load
In this module we will introduce you to data processing architectures in Google Cloud Platform: Asynchronous processing with TaskQueues. Message-oriented architectures with Pub/Sub. Creating pipelines with Dataflow.
4 видео ((всего 9 мин.)), 1 материал для самостоятельного изучения, 1 тест
4 видео
Message-oriented Architectures3мин
Serverless Data Pipelines3мин
Module Review32
1 материал для самостоятельного изучения
Module Resources5мин
1 практическое упражнение
Module Review4мин
Summary of GCP, Big Data and ML
3 видео ((всего 5 мин.)), 1 материал для самостоятельного изучения
1 материал для самостоятельного изучения
Additional Resources10мин
51%
начал новую карьеру, пройдя эти курсы
47%
получил значимые преимущества в карьере благодаря этому курсу
Лучшие рецензии
автор: CR•Dec 27th 2017
This was a great course to understand at a high level how to design and create my data ecosystem and how to do it sustainably. Hopefully, next courses provide more in-depth the technical features.
автор: JI•Mar 27th 2018
Very good and well thought out.\n\nI just laughed out loud when the translation for "wow this is cool" to Spanish was "wow esto es fresco" (wow, this is a fresco/fresh) Classic google translate.
О 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.
О специализации ''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
>>> 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 <<<
Часто задаваемые вопросы
Когда я получу доступ к лекциям и заданиям?
Зарегистрировавшись на сертификацию, вы получите доступ ко всем видео, тестам и заданиям по программированию (если они предусмотрены). Задания по взаимной оценке сокурсниками можно сдавать и проверять только после начала сессии. Если вы проходите курс без оплаты, некоторые задания могут быть недоступны.
Что я получу, оформив подписку на специализацию?
Записавшись на курс, вы получите доступ ко всем курсам в специализации, а также возможность получить сертификат о его прохождении. После успешного прохождения курса на странице ваших достижений появится электронный сертификат. Оттуда его можно распечатать или прикрепить к профилю LinkedIn. Просто ознакомиться с содержанием курса можно бесплатно.
Какие правила возврата средств?
Можно ли получить финансовую помощь?
Are there prerequisites for this course?
Before enrolling in this course, participants should have roughly one (1) year of experience with one or more of the following:
• A common query language such as SQL
• Extract, transform, load activities
• Data modeling
• Machine learning and/or statistics
• Programming in Python
Am I eligible for the Google Cloud Platform free trial?
To be eligible for the free trial, you will need:
- Google account (Google is currently blocked in China)
- Credit card or bank account
- Terms of service
Note: There is a known issue with certain EU countries where individuals are not able to sign up, but you may sign up as "business" status and intend to see a potential economic benefit from the trial. More details at: https://support.google.com/cloud/answer/6090602
More Google Cloud Platform free trial FAQs are available at: https://cloud.google.com/free-trial/
For more details on how the free trial works, visit our documentation page: https://cloud.google.com/free-trial/docs/
What if I have already used up my Google Cloud Platform free trial?
If your current Google account is no longer eligible for the Google Cloud Platform free trial, you can create another Google account. Your new Google account should be used to sign up for the free trial.
How does the free trial work?
View this page for more details: https://cloud.google.com/free-trial/docs/
Is this course similar to CPB100?
Yes, this online course is based on the instructor-led training formerly known as CPB100.
Does this course relate to the Google Certified Professional Data Engineer certification?
The course covers the topics presented on the certification exam, however we recommend additional preparation including hands-on product experience. The best preparation for certification is real-world, hands-on experience. Review the Google Certified Professional Data Engineer certification preparation guide for further information and resources at https://cloud.google.com/certification/guides/data-engineer/
What is a Google certification?
Google’s Certification Program gives customers and partners a way to demonstrate their technical skills in a particular job-role and technology. Individuals are assessed using a variety of rigorously developed industry-standard methods to determine whether they meet Google’s proficiency standards. Read more at https://cloud.google.com/certification/
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