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
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Специализация Data Engineering on Google Cloud Platform
Data Engineering on Google Cloud Platform. Launch your career in Data Engineering. Deliver business value with big data and machine learning.
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Специализация: принцип работы
Пройти курсы
Специализация Coursera — это серия курсов, помогающих в совершенстве овладеть определенным навыком. Можно сразу записаться на специализацию или просмотреть курсы, из которых она состоит и выбрать тот, с которого вы хотите начать. Подписываясь на курс, который входит в специализацию, вы автоматически подписываетесь на всю специализацию. Можно завершить всего один курс, а потом сделать паузу в обучении или в любой момент отменить подписку. Отслеживайте свои курсы и прогресс на панели управления учащегося.
Практический проект
В каждой специализации есть практический проект, который нужно успешно выполнить, чтобы завершить специализацию и получить сертификат. Если для практического проекта в специализации предусмотрен отдельный курс, прежде чем начать его, необходимо завершить все остальные курсы.
Получите сертификат
Когда вы пройдете все курсы и завершите практический проект, вы получите сертификат, которым можно поделиться с потенциальными работодателями и коллегами.
Специализация включает несколько курсов: 5
Курс1
Google Cloud Platform Big Data and Machine Learning Fundamentals
4.6
Оценки: 4,585
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/
Курс2
Leveraging Unstructured Data with Cloud Dataproc on Google Cloud Platform
4.5
Оценки: 2,333
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
Курс3
Serverless Data Analysis with Google BigQuery and Cloud Dataflow
4.5
Оценки: 1,781
This 1-week, accelerated on-demand course builds upon Google Cloud Platform Big Data and Machine Learning Fundamentals. Through a combination of instructor-led presentations, demonstrations, and hands-on labs, students learn how to carry out no-ops data warehousing, analysis and pipeline processing.
Prerequisites:
• Google Cloud Platform Big Data and Machine Learning Fundamentals
• Experience using a SQL-like query language to analyze data
• Knowledge of either Python or Java
Google Account Notes:
• Google services are currently unavailable in China.
Курс4
Serverless Machine Learning with Tensorflow on Google Cloud Platform
4.4
Оценки: 1,437
This one-week accelerated on-demand course provides participants a a hands-on introduction to designing and building machine learning models on Google Cloud Platform. Through a combination of presentations, demos, and hand-on labs, participants will learn machine learning (ML) and TensorFlow concepts, and develop hands-on skills in developing, evaluating, and productionizing ML models.
OBJECTIVES
This course teaches participants the following skills:
● Identify use cases for machine learning
● Build an ML model using TensorFlow
● Build scalable, deployable ML models using Cloud ML
● Know the importance of preprocessing and combining features
● Incorporate advanced ML concepts into their models
● Productionize trained ML models
PREREQUISITES
To get the most of out of this course, participants should have:
● Completed Google Cloud Fundamentals- Big Data and Machine Learning course OR have equivalent experience
● Basic proficiency with common query language such as SQL
● Experience with data modeling, extract, transform, load activities
● Developing applications using a common programming language such Python
● Familiarity with Machine Learning and/or statistics
Google Account Notes:
• Google services are currently unavailable in China.
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.
Часто задаваемые вопросы
Какие правила возврата средств?
Можно ли зарегистрироваться только на один курс?
Да! Чтобы начать, нажмите карточку интересующего вас курса и зарегистрируйтесь. Зарегистрировавшись, вы можете пройти курс и получить сертификат, ссылкой на который можно делиться с другими людьми. Просто ознакомиться с содержанием курса можно бесплатно. При подписке на курс, входящий в специализацию, вы автоматически подписываетесь на всю специализацию. Ход учебы можно отслеживать в панели управления учащегося.
Можно ли получить финансовую помощь?
Могу ли я пройти курс бесплатно?
Действительно ли это полностью дистанционный курс? Нужно ли мне посещать какие-либо занятия лично?
Это полностью дистанционный курс, потому вам не нужно ничего посещать. Все лекции, материалы для самостоятельного изучения и задания доступны всегда и везде по Интернету и с мобильных устройств.
Получу ли я зачеты в университете за прохождение специализации?
Эта специализация не приравнивается к зачету в университетах, однако некоторые вузы принимают сертификаты на свое усмотрение. Дополнительную информацию уточняйте в своем деканате.
Сколько времени занимает получение специализации?
This accelerated specialization is designed to be completed in only four weeks. Additionally, our Google Cloud Platform free trial ends after 60 days or when your $300 in credits are used up.
What background knowledge is necessary?
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
Do I need to take the courses in a specific order?
We strongly recommend you take these courses in order, beginning with Big Data and Machine Learning Fundamentals. This is especially important when completing the Google Codelabs projects, as these hands-on labs build upon the work you complete in preceding courses.
What will I be able to do upon completing the Specialization?
Google Cloud Platform is used in a wide variety of environments, all the way from startups to global enterprises. This specialization is designed to help prepare you to implement solutions using Google Cloud Platform in any of these types of environments.
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\n\nMore 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 the certificate received after completing a Coursera course or specialization the same as a Google Cloud certification?
No, the certificate received is a Coursera coursework completion certificate and not an official Google Cloud certification. To receive a Google Cloud certification you need to pass a Google Cloud certification exam which must be taken in-person at an official testing center. More information available here: https://cloud.google.com/certification/
I’ve passed all the Coursera courses for the Data Engineering on Google Cloud Platform Specialization. Will I be able to pass the Google Certified Professional Data Engineer certification exam?
Taking courses is a great way to familiarize yourself with the various components of Google Cloud Platform; however, actual real-world, hands-on experience is the best preparation for certification. Combine these courses and work experience and you are on your way to certification.
Остались вопросы? Посетите Центр поддержки учащихся.
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