Informações sobre o curso
100% online

100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Nível intermediário

Nível intermediário

Horas para completar

Aprox. 4 horas para completar

Sugerido: Einwöchiger Kurs, 8–12 Stunden/Woche...
Idiomas disponíveis

Alemão

Legendas: Alemão, Francês, Japonês, Inglês
100% online

100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Nível intermediário

Nível intermediário

Horas para completar

Aprox. 4 horas para completar

Sugerido: Einwöchiger Kurs, 8–12 Stunden/Woche...
Idiomas disponíveis

Alemão

Legendas: Alemão, Francês, Japonês, Inglês

Programa - O que você aprenderá com este curso

Semana
1
Horas para completar
11 minutos para concluir

Willkommen zum serverlosen maschinellen Lernen mit der Google Cloud Platform

...
Reading
2 vídeos (total de (Total 5 mín.) min), 1 teste
Video2 videos
Überlegungen zum maschinellen Lernen2min
Quiz1 exercício prático
ML-Kurs – Vorabfragen6min
Horas para completar
3 horas para concluir

Modul 1: Einführung in maschinelles Lernen

...
Reading
21 vídeos (total de (Total 109 mín.) min), 2 testes
Video21 videos
Arten von ML3min
Die ML-Pipeline2min
Varianten des ML-Modells7min
ML-Problem eingrenzen2min
Maschinelles Lernen (ML) ausprobieren8min
Optimierung9min
Sichere Testumgebung für neuronale Netzwerke18min
Funktionen kombinieren3min
Feature Engineering3min
Bildmodelle5min
Effektives ML2min
Was macht ein gutes Dataset aus?5min
Fehlermesswerte3min
Genauigkeit2min
Genauigkeit und Trefferquote5min
Datasets für maschinelles Lernen erstellen3min
Datasets aufteilen6min
Python-Notebooks1min
Übersicht zum Lab "Datasets für maschinelles Lernen erstellen"3min
Zusammenfassung zum Lab "Datasets für maschinelles Lernen erstellen"2min
Quiz1 exercício prático
Quiz zu Modul 18min
Horas para completar
5 horas para concluir

Modul 2: ML-Modelle mit TensorFlow erstellen

...
Reading
15 vídeos (total de (Total 65 mín.) min), 5 testes
Video15 videos
Was ist TensorFlow?5min
Core TensorFlow5min
Übersicht zum Lab "Einführung in TensorFlow"7s
Zusammenfassung zum TensorFlow-Lab10min
Estimator API8min
Maschinelles Lernen mit tf.estimator15s
Zusammenfassung zum Lab "Estimator"7min
Effektives ML ermöglichen6min
Einführung zum Lab "Refaktorierung zum Hinzufügen von Stapelverarbeitung und Funktionserstellung"38s
Zusammenfassung zum Lab "Refaktorierung"4min
Trainieren und Bewerten4min
Monitoring1min
Einführung zum Lab "Verteiltes Training und Monitoring"2min
Zusammenfassung zum Lab "Verteiltes Training und Monitoring"7min
Quiz1 exercício prático
Quiz zu Modul 28min
Horas para completar
2 horas para concluir

Modul 3: ML-Modelle mit Cloud ML Engine skalieren

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Reading
7 vídeos (total de (Total 28 mín.) min), 2 testes
Video7 videos
Vorteile der Cloud ML Engine6min
Arbeitsablauf bei der Entwicklung1min
Trainingspakete erstellen3min
TensorFlow bereitstellen3min
Lab: ML hochskalieren39s
Zusammenfassung zum Lab "ML hochskalieren"10min
Quiz1 exercício prático
Quiz für Modul 34min
Horas para completar
3 horas para concluir

Modul 4: Feature Engineering

...
Reading
16 vídeos (total de (Total 92 mín.) min), 2 testes
Video16 videos
Gute Funktionen7min
Kausalität8min
Numerisch5min
Ausreichende Beispiele7min
Von den Rohdaten zur Funktion1min
Kategoriale Merkmale8min
Funktionsverknüpfungen3min
Bucketizing3min
Breit und tief5min
Einsatzbereiche für Feature Engineering3min
Überblick zum Lab "Feature Engineering"3min
Zusammenfassung zum Lab "Feature Engineering"10min
Hyperparameter-Abstimmung + Demo15min
ML-Abstraktionsebenen4min
Fazit1min
Quiz1 exercício prático
Quiz zu Modul 46min

Sobre 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....

Sobre o Programa de cursos integrados Data Engineering on Google Cloud Platform auf Deutsch

Dieser fünfwöchige Onlinevertiefungskurs bietet eine praktische Einführung zum Entwerfen und Erstellen von Datenverarbeitungssystemen auf der Google Cloud Platform. In Präsentationen, Demos und praxisorientierten Labs entwickeln die Teilnehmer Datenverarbeitungssysteme, erstellen End-to-End-Datenpipelines, analysieren Daten und üben maschinelles Lernen. Der Kurs umfasst strukturierte, unstrukturierte und gestreamte Daten. Dieser Kurs vermittelt den Teilnehmern die folgenden Kompetenzen: • Datenverarbeitungssysteme auf der Google Cloud Platform entwickeln • Unstrukturierte Daten mit Spark und ML-APIs auf Cloud Dataproc verwenden • Batch- und Streaming-Daten durch die Implementierung von Autoscaling-Datenpipelines auf Cloud Dataflow verarbeiten • Mit Google BigQuery Geschäftsinformationen aus extrem großen Datasets ableiten • Modelle des maschinellen Lernens mit TensorFlow und Cloud ML trainieren, auswerten und damit Vorhersagen treffen • Sofortige Statistiken aus Streaming-Daten ermöglichen Dieser Kurs richtet sich an erfahrene Entwickler, die für die Verwaltung von Big Data-Transformationen verantwortlich sind, zum Beispiel: • Daten extrahieren, laden, transformieren, bereinigen und validieren • Pipelines und Architekturen für die Datenverarbeitung entwerfen • Modelle des maschinellen Lernens und der Statistik erstellen und warten • Datasets abfragen, Abfrageergebnisse visualisieren und Berichte erstellen...
Data Engineering on Google Cloud Platform auf Deutsch

Perguntas Frequentes – FAQ

  • 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, when available.

  • Before enrolling in this course, participants should have roughly one (1) year of experience with one or more of the following:

    • Knowledge of Google Cloud Platform

    • Big Data & Machine Learning Fundamentals to the level of "Google Cloud Platform Big Data and Machine Learning Fundamentals" on Coursera

    • Knowledge of BigQuery and Dataflow to the level of "Serverless Data Analysis with Google BigQuery and Cloud Dataflow" on Coursera

    • Knowledge of Python and familiarity with the numpy package

    • Knowledge of undergraduate-level statistics to the level of a Basic Statistics course on Coursera

  • 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/

  • 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.

  • View this page for more details: https://cloud.google.com/free-trial/docs/

  • Yes, this online course is based on the instructor-led training formerly known as CPB102.

  • 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/

  • 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/

Mais dúvidas? Visite o Central de Ajuda ao Aprendiz.