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Smart Analytics, Machine Learning, and AI on GCP em Português Brasileiro
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Google Cloud

Smart Analytics, Machine Learning, and AI on GCP em Português Brasileiro

This course is part of Data Engineer, Big Data and ML on Google Cloud em Português Specialization

Google Cloud Training

Instructor: Google Cloud Training

Included with Coursera Plus

•Learn more
9 modules
Gain insight into a topic and learn the fundamentals.
4.7

(11 reviews)

Intermediate level
Some related experience required
7 hours to complete
Flexible schedule
Learn at your own pace

9 modules
Gain insight into a topic and learn the fundamentals.
4.7

(11 reviews)

Intermediate level
Some related experience required
7 hours to complete
Flexible schedule
Learn at your own pace
  • About
  • Outcomes
  • Modules
  • Recommendations
  • Testimonials

What you'll learn

  • Saber a diferença entre ML, IA e aprendizado profundo.

  • Explicar o uso de APIs de ML em dados não estruturados.

  • Executar comandos do BigQuery nos Notebooks.

  • Criar modelos de ML usando a sintaxe do SQL no BigQuery.

Skills you'll gain

  • Machine Learning
  • Unstructured Data
  • Analytics
  • Applied Machine Learning
  • Big Data
  • Tensorflow
  • Jupyter
  • Google Cloud Platform
  • Data Pipelines
  • Artificial Intelligence and Machine Learning (AI/ML)

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

6 assignments

Taught in Portuguese (Brazil)

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Build your subject-matter expertise

This course is part of the Data Engineer, Big Data and ML on Google Cloud em Português Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 9 modules in this course

A incorporação de machine learning em pipelines de dados aumenta a capacidade de extrair insights dessas informações. Neste curso, mostramos as várias formas de incluir essa tecnologia em pipelines de dados do Google Cloud. Para casos de pouca ou nenhuma personalização, vamos falar sobre o AutoML. Para usar recursos de machine learning mais personalizados, vamos apresentar os Notebooks e o machine learning do BigQuery (BigQuery ML). No curso, você também vai aprender sobre a produção de soluções de machine learning usando a Vertex AI.

Neste módulo, vamos apresentar o curso e a programação.

What's included

1 video

1 video•Total 1 minute
  • Introdução ao curso•1 minute•Preview module

Neste módulo, falamos sobre as opções de ML no Google Cloud.

What's included

4 videos1 assignment

4 videos•Total 8 minutes
  • Introdução ao módulo•0 minutes•Preview module
  • O que é IA?•4 minutes
  • Da análise de dados ad hoc às decisões orientadas por dados•1 minute
  • Opções para modelos de ML no Google Cloud•1 minute
1 assignment•Total 10 minutes
  • Introdução ao Analytics e à IA•10 minutes

O foco deste módulo é o uso de APIs de ML pré-criadas em dados não estruturados.

What's included

5 videos1 assignment1 app item

5 videos•Total 13 minutes
  • Introdução ao módulo•0 minutes•Preview module
  • Os dados não estruturados são complicados•3 minutes
  • APIs de ML para enriquecimento de dados•3 minutes
  • Introdução ao laboratório: Como usar a API Natural Language para classificar textos não estruturados•0 minutes
  • Coursera: Introdução ao Google Cloud Platform e o Qwiklabs•4 minutes
1 assignment•Total 10 minutes
  • APIs de modelos de ML pré-criadas para dados não estruturados•10 minutes
1 app item•Total 60 minutes
  • Laboratório: Como usar a API Natural Language para classificar textos não estruturados•60 minutes

Neste módulo, vamos falar sobre como usar o Notebooks.

What's included

4 videos1 assignment1 app item

4 videos•Total 6 minutes
  • Introdução ao módulo•0 minutes•Preview module
  • O que é um notebook?•4 minutes
  • O recurso mágico do BigQuery e vínculos ao Pandas•1 minute
  • Introdução ao laboratório: BigQuery no JupyterLab na Vertex AI•0 minutes
1 assignment•Total 10 minutes
  • Análise de Big Data com os Notebooks•10 minutes
1 app item•Total 75 minutes
  • Laboratório: BigQuery no JupyterLab na Vertex AI•75 minutes

Neste módulo, falamos da criação de modelos de ML personalizados e apresentamos a Vertex AI e o TensorFlow Hub.

What's included

6 videos1 assignment1 app item

6 videos•Total 7 minutes
  • Introdução ao módulo•0 minutes•Preview module
  • Maneiras de usar ML no Google Cloud•1 minute
  • Vertex AI Pipelines•3 minutes
  • TensorFlow Hub•0 minutes
  • Introdução ao laboratório: Como executar pipelines na Vertex AI•0 minutes
  • Resumo•0 minutes
1 assignment•Total 10 minutes
  • Pipelines de ML na produção•10 minutes
1 app item•Total 60 minutes
  • Laboratório: Como executar pipelines na Vertex AI•60 minutes

Este é um módulo sobre o BigQuery ML.

What's included

6 videos1 assignment2 app items

6 videos•Total 12 minutes
  • Introdução ao módulo•0 minutes•Preview module
  • BigQuery ML para criação rápida de modelos•3 minutes
  • Modelos com suporte•7 minutes
  • Introdução ao laboratório: Prever a duração de um trajeto de bicicleta com um modelo de regressão no BigQuery ML•0 minutes
  • Introdução ao laboratório: Recomendações de filmes no BigQuery ML•0 minutes
  • Resumo•0 minutes
1 assignment•Total 10 minutes
  • Criação de modelo personalizado com SQL no BigQuery ML•10 minutes
2 app items•Total 120 minutes
  • Prever a duração de um trajeto de bicicleta com um modelo de regressão no BigQuery ML•60 minutes
  • Laboratório: Recomendações de filmes no BigQuery ML•60 minutes

Criar modelos personalizados com o Vertex AI AutoML.

What's included

6 videos1 assignment

6 videos•Total 22 minutes
  • Introdução ao módulo•0 minutes•Preview module
  • Por que usar o AutoML?•10 minutes
  • AutoML Vision•2 minutes
  • Processamento de linguagem natural do AutoML•2 minutes
  • AutoML Tables•6 minutes
  • Resumo•0 minutes
1 assignment•Total 10 minutes
  • Criação de modelo personalizado com o AutoML •10 minutes

Neste módulo, vamos recapitular os temas abordados no curso.

What's included

1 video

1 video
  • Resumo do curso•0 minutes•Preview module

Links dos PDFs de todos os módulos

What's included

1 reading

1 reading•Total 10 minutes
  • Smart Analytics, Machine Learning and AI on Google Cloud•10 minutes

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Instructor

Google Cloud Training
Google Cloud Training
Google Cloud
1,902 Courses•3,519,073 learners

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Google Cloud

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Frequently asked questions

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.

If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policyOpens in a new tab.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

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