Microsoft Azure Fundamentals—Is It Worth It?
July 26, 2024
Article
This course is part of Data Engineer, Big Data and ML on Google Cloud em Português Specialization
Instructor: Google Cloud Training
Included with
(11 reviews)
(11 reviews)
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.
Add to your LinkedIn profile
6 assignments
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
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.
Neste módulo, falamos sobre as opções de ML no Google Cloud.
4 videos1 assignment
O foco deste módulo é o uso de APIs de ML pré-criadas em dados não estruturados.
5 videos1 assignment1 app item
Neste módulo, vamos falar sobre como usar o Notebooks.
4 videos1 assignment1 app item
Neste módulo, falamos da criação de modelos de ML personalizados e apresentamos a Vertex AI e o TensorFlow Hub.
6 videos1 assignment1 app item
Este é um módulo sobre o BigQuery ML.
6 videos1 assignment2 app items
Criar modelos personalizados com o Vertex AI AutoML.
6 videos1 assignment
Neste módulo, vamos recapitular os temas abordados no curso.
Links dos PDFs de todos os módulos
1 reading
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.
Course
Course
Course
Course
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Earn a degree from world-class universities - 100% online
Upskill your employees to excel in the digital economy
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 policy.
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.