Informações sobre o curso
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Nível intermediário

Aprox. 12 horas para completar

Sugerido: 1 week of study, 6-10 hours/week...

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Legendas: Inglês

Habilidades que você terá

TensorflowBigqueryGoogle Cloud PlatformCloud Computing

100% online

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Nível intermediário

Aprox. 12 horas para completar

Sugerido: 1 week of study, 6-10 hours/week...

Inglês

Legendas: Inglês

Programa - O que você aprenderá com este curso

Semana
1
3 horas para concluir

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.

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13 vídeos ((Total 78 mín.)), 2 leituras, 2 testes
13 videos
Demo: Creating a VM on Compute Engine13min
Elastic Storage with Google Cloud Storage5min
Build on Google's Global Network3min
Security: On-premise vs Cloud-native2min
Evolution of Google Cloud Big Data Tools5min
Getting Started with Google Cloud Platform and Qwiklabs3min
Choosing the right approach5min
What you can do with Google Cloud Platform3min
Activity: Explore real customer solution architectures7min
Key roles in a data-driven organization6min
2 leituras
Google Cloud Public Datasets program10min
Module Resources10min
1 exercício prático
Module Review5min
2 horas para concluir

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.

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8 vídeos ((Total 50 mín.)), 1 leitura, 2 testes
8 videos
Approach: Move from on-premise to Google Cloud Platform9min
Demo: From zero to an Apache Spark job in 10 minutes or less6min
Challenge: Utilizing and tuning on-premise clusters6min
Move storage off-cluster with Google Cloud Storage4min
Lab Intro2min
1 leituras
Module Resources5min
1 exercício prático
Module Review15min
3 horas para concluir

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.

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13 vídeos ((Total 74 mín.)), 2 leituras, 2 testes
13 videos
Demo: Exploring bike share data with SQL11min
Data quality4min
BigQuery managed storage5min
Insights from geographic data2min
Demo: Analyzing lightning strikes with BigQuery GIS7min
Choosing a ML model type for structured data4min
Predicting customer lifetime value5min
BigQueryML: Create models with SQL3min
Phases in ML model lifecycle2min
BigQuery ML: key features walkthrough5min
2 leituras
Lab Intro10min
Module Resources10min
1 exercício prático
Module Review4min
Semana
2
2 horas para concluir

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.

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8 vídeos ((Total 31 mín.)), 1 leitura, 2 testes
8 videos
Implementing streaming pipelines on Cloud Dataflow3min
Visualizing insights with Data Studio3min
Creating charts with Data Studio2min
Demo: Data Studio walkthrough7min
Lab Intro1min
1 leituras
Module Resources10min
1 exercício prático
Module Review4min
2 horas para concluir

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.

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10 vídeos ((Total 55 mín.)), 2 leituras, 2 testes
10 videos
Comparing approaches to ML2min
Demo: Using ML building blocks7min
Using pre-built AI to create a chatbot4min
Customizing Pre-built models with AutoML7min
Lab Intro22s
Building a Custom Model1min
Demo: Text classification done three ways21min
2 leituras
Additional resources to build custom models10min
Module Resources10min
1 exercício prático
Module Review
5 minutos para concluir

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.

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1 vídeo ((Total 5 mín.))
1 vídeos
4.6
1177 avaliaçõesChevron Right

45%

comecei uma nova carreira após concluir estes cursos

42%

consegui um benefício significativo de carreira com este curso

Principais avaliações do Google Cloud Platform Big Data and Machine Learning Fundamentals

por VSMar 3rd 2019

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.

por CRDec 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.

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, Big Data, and Machine Learning on GCP

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 <<<...
Data Engineering, Big Data, and Machine Learning on GCP

Perguntas Frequentes – FAQ

  • Ao se inscrever para um Certificado, você terá acesso a todos os vídeos, testes e tarefas de programação (se aplicável). Tarefas avaliadas pelos colegas apenas podem ser enviadas e avaliadas após o início da sessão. Caso escolha explorar o curso sem adquiri-lo, talvez você não consiga acessar certas tarefas.

  • Quando você se inscreve no curso, tem acesso a todos os cursos na Especialização e pode obter um certificado quando concluir o trabalho. Seu Certificado eletrônico será adicionado à sua página de Participações e você poderá imprimi-lo ou adicioná-lo ao seu perfil no LinkedIn. Se quiser apenas ler e assistir o conteúdo do curso, você poderá frequentá-lo como ouvinte sem custo.

  • 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

  • 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 CPB100.

  • 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/

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