What are best practices for implementing machine learning on Google Cloud? What is Vertex AI and how can you use the platform to quickly build, train, and deploy AutoML machine learning models without writing a single line of code? What is machine learning, and what kinds of problems can it solve?
How Google does Machine Learning
Über diesen Kurs
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Was Sie lernen werden
Describe Vertex AI Platform and how it's used to quickly build, train,and deploy AutoML machine learning models without writing a single line of code
Describe best practices for implementing machine learning on Google Cloud
Leverage Google Cloud Platform tools and environment to do ML
Articulate Responsible AI best practices
Kompetenzen, die Sie erwerben
- Application Programming Interfaces (API)
- Inclusive ML
- Machine Learning
- Google Cloud Platform
Könnte Ihr Unternehmen von Mitarbeiterweiterbildungen für gefragte Kompetenzen profitieren?Probieren Sie Coursera for Business aus
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.
Lehrplan - Was Sie in diesem Kurs lernen werden
Introduction to Course and Series
This module introduces the course series and the Google experts who will be teaching it.
What It Means to be AI-First
In this module, you explore building a data strategy around machine learning.
How Google Does ML
This module shares the organizational know-how Google has acquired over the years.
Machine Learning Development with Vertex AI
All machine learning starts with some type of goal - whether it be a business use case, academic use case, or goal you are trying to solve. This module reviews the process of determining whether the model is ready for production the “proof of concept” or “experimentation” phase.
Machine Learning Development with Vertex Notebooks
This module explores both managed notebooks and user-managed notebooks for machine learning development in Vertex AI.
Best Practices for Implementing Machine Learning on Vertex AI
This module reviews best practices for a number of different machine learning processes in Vertex AI.
Responsible AI Development
This module discusses why machine learning systems aren’t fair by default and some of the things you have to keep in mind as you infuse ML into your products.
This module is a summary of the How Google Does Machine Learning course.
- 5 stars68,98 %
- 4 stars23,71 %
- 3 stars5,25 %
- 2 stars1,13 %
- 1 star0,91 %
Top-Bewertungen von HOW GOOGLE DOES MACHINE LEARNING
Great to know how to do machine learning in scale and to know the common pitfalls people may fall into while doing ML. Provides great hands-on training on GCP and get to know various API's GCP offers.
This is a good introductory course on how actually Machine Learning is being developed in Companies like Google. It covers the basic aspects of how ML is done using Cloud Platform using Cloud APIs.
I actually learnt lot of good stuff regarding GCP and ML on cloud. This is the beginner course for anyone who wants to start off their career in GCP and ML. Thanks coursera and GCP for this course
The course covers lots of best practices when transferring an organization into a ML organization. It's not too technical but covers high-level concepts and know-how. I really like it
Häufig gestellte Fragen
Wann erhalte ich Zugang zu den Vorträgen und Aufgaben?
Der Zugang zu Vorlesungen und Aufgaben hängt von der Art Ihrer Anmeldung ab. Wenn Sie einen Kurs im Gastmodus belegen, können Sie die meisten Kursmaterialien kostenlos einsehen. Um auf benotete Aufgaben zuzugreifen und ein Zertifikat zu erhalten, müssen Sie während oder nach Ihrer Gastphase das Zertifikat erwerben. Wenn Sie die Gastoption nicht sehen:
Der Kurs bietet möglicherweise keine Gastoption an. Sie können stattdessen eine kostenlose Testversion ausprobieren oder finanzielle Unterstützung beantragen.
Der Kurs kann stattdessen "Vollständiger Kurs ohne Zertifikat" anbieten. Mit dieser Option können Sie alle Kursmaterialien einsehen, die erforderlichen Aufgaben einreichen und eine Endnote erhalten. Dies bedeutet auch, dass Sie kein Zertifikat erwerben können.
Was bekomme ich, wenn ich dieses Zertifikat abonniere?
Wenn Sie sich für den Kurs anmelden, erhalten Sie Zugriff auf alle Kurse des Zertifikats 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 lediglich den Inhalt des Kurses lesen und anzeigen möchten, können Sie kostenlos als Gast an dem Kurs teilnehmen.
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Last Updated: September 1, 2015
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