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.
Dieser Kurs ist Teil der Spezialisierung Spezialisierung Data Engineering on Google Cloud Platform
Google Cloud Platform Big Data and Machine Learning Fundamentals
4.6
(5,705 ratings)
60,523 bereits angemeldet!
von
Über diesen Kurs
322,009
322,009Kompetenzen, die Sie erwerben
TensorflowBigqueryGoogle Cloud PlatformCloud Computing
Lehrplan - Was Sie in diesem Kurs lernen werden
Woche
13 Stunden zum Abschließen
Introduction to the Data and Machine Learning on Google Cloud Platform Specialization
Welcome to the Big Data and Machine Learning fundamentals on GCP course. Here you will learn the basics of how the course is structured and the four main big data challenges you will solve for.
13 Videos (Gesamt 78 min), 2 Lektüren, 2 Quiz
13 Videos
Introduction to Google Cloud Platform3m
Compute Power for Analytic and ML Workloads9m
Demo: Creating a VM on Compute Engine13m
Elastic Storage with Google Cloud Storage5m
Build on Google's Global Network3m
Security: On-premise vs Cloud-native2m
Evolution of Google Cloud Big Data Tools5m
Getting Started with Google Cloud Platform and Qwiklabs3m
Choosing the right approach5m
What you can do with Google Cloud Platform3m
Activity: Explore real customer solution architectures7m
Key roles in a data-driven organization6m
2 Lektüren
Google Cloud Public Datasets program10m
Module Resources10m
1 praktische Übung
Module Review5m
2 Stunden zum Abschließen
Recommending Products using Cloud SQL and Spark
In this module you will have an existing Apache SparkML recommendation model that is running on-premise. You will learn about recommendation models and how you can run them in the cloud with Cloud Dataproc and Cloud SQL.
8 Videos (Gesamt 50 min), 1 Lektüre, 2 Quiz
8 Videos
Introduction to machine learning5m
Challenge: ML for recommending housing rentals8m
Approach: Move from on-premise to Google Cloud Platform9m
Demo: From zero to an Apache Spark job in 10 minutes or less6m
Challenge: Utilizing and tuning on-premise clusters6m
Move storage off-cluster with Google Cloud Storage4m
Lab Intro2m
1 Lektüre
Module Resources5m
1 praktische Übung
Module Review15m
3 Stunden zum Abschließen
Predict Visitor Purchases with BigQuery ML
In this module, you will learn the foundations of BigQuery and big data analysis at scale. You will then learn how to build your own custom machine learning model to predict visitor purchases using just SQL with BigQuery ML.
13 Videos (Gesamt 74 min), 2 Lektüren, 2 Quiz
13 Videos
Demo: Query 2 billion lines of Github code in less than 30 seconds11m
BigQuery: Fast SQL Engine4m
Demo: Exploring bike share data with SQL11m
Data quality4m
BigQuery managed storage5m
Insights from geographic data2m
Demo: Analyzing lightning strikes with BigQuery GIS7m
Choosing a ML model type for structured data4m
Predicting customer lifetime value5m
BigQueryML: Create models with SQL3m
Phases in ML model lifecycle2m
BigQuery ML: key features walkthrough5m
2 Lektüren
Lab Intro10m
Module Resources10m
1 praktische Übung
Module Review4m
Woche
22 Stunden zum Abschließen
Create Streaming Data Pipelines with Cloud Pub/sub and Cloud Dataflow
In this module you will engineer and build an auto-scaling streaming data pipeline to ingest, process, and visualize data on a dashboard. Before you build your pipeline you'll learn the foundations of message-oriented architecture and pitfalls to avoid when designing and implementing modern data pipelines.
8 Videos (Gesamt 31 min), 1 Lektüre, 2 Quiz
8 Videos
Message-oriented architectures with Cloud Pub/Sub6m
Designing streaming pipelines with Apache Beam3m
Implementing streaming pipelines on Cloud Dataflow3m
Visualizing insights with Data Studio3m
Creating charts with Data Studio2m
Demo: Data Studio walkthrough7m
Lab Intro1m
1 Lektüre
Module Resources10m
1 praktische Übung
Module Review4m
2 Stunden zum Abschließen
Classify Images with Pre-Built Models using Vision API and Cloud AutoML
Don't want to create a custom ML model from scratch? Learn how to leverage and extend pre-built ML models like the Vision API and Cloud AutoML for image classification.
10 Videos (Gesamt 55 min), 2 Lektüren, 2 Quiz
10 Videos
How does ML on unstructured data work?3m
Demo: ML built into Google Photos1m
Comparing approaches to ML2m
Demo: Using ML building blocks7m
Using pre-built AI to create a chatbot4m
Customizing Pre-built models with AutoML7m
Lab Intro22
Building a Custom Model1m
Demo: Text classification done three ways21m
2 Lektüren
Additional resources to build custom models10m
Module Resources10m
1 praktische Übung
Module Review
5 Minuten zum Abschließen
Summary
In this final module, we will review the key challenges, solutions, and topics covered as part of this fundamentals course. We will also review additional resources and the steps you can take to get certified as a Google Cloud Data Engineer.
1 Video (Gesamt 5 min)
1 Video
47%
nahm einen neuen Beruf nach Abschluss dieser Kurse auf
43%
ziehen Sie für Ihren Beruf greifbaren Nutzen aus diesem Kurs
Top-Bewertungen
Overall a good curated course to help understand the GCP offerings and high level architecture of how their offerings fit in the current landscape. Easy to follow along as this was fundamental course.
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.
Über 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.
Über die Spezialisierung 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 <<<
Häufig gestellte Fragen
Wann erhalte ich Zugang zu den Vorträgen und Aufgaben?
Sobald Sie sich für ein Zertifikat angemeldet haben, haben Sie Zugriff auf alle Videos, Quizspiele und Programmieraufgaben (falls zutreffend). Aufgaben, die von anderen Kursteilnehmern bewertet werden, können erst dann eingereicht und überprüft werden, wenn Ihr Unterricht begonnen hat. Wenn Sie sich den Kurs anschauen möchten, ohne ihn zu kaufen, können Sie womöglich auf bestimmte Aufgaben nicht zugreifen.
Was bekomme ich, wenn ich diese Spezialisierung abonniere?
Wenn Sie sich für den Kurs anmelden, erhalten Sie Zugriff auf alle Kurse der Spezialisierung und Sie erhalten nach Abschluss aller Arbeiten ein Zertifikat. Ihr elektronisches Zertifikat wird zu Ihrer Seite „Errungenschaften“ hinzugefügt – von dort können Sie Ihr Zertifikat ausdrucken oder es zu Ihrem LinkedIn Profil hinzufügen. Wenn Sie nur lesen und den Inhalt des Kurses anzeigen möchten, können Sie kostenlos als Gast an dem Kurs teilnehmen.
Wie erfolgen Rückerstattungen?
Ist finanzielle Unterstützung möglich?
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/
Haben Sie weitere Fragen? Besuchen Sie das Hilfe-Center für Teiln..
Coursera arbeitet mit erstklassigen Universitäten und Organisationen zusammen, um Online-Kurse anzubieten und dadurch universellen Zugriff auf die weltweit beste Ausbildung zu ermöglichen.
© 2019 Coursera Inc. Alle Rechte vorbehalten.
