Informações sobre o curso
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Prazos flexíveis

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Nível intermediário

Aprox. 11 horas para completar

Sugerido: 1 week of study, 8-12 hours/week...

Inglês

Legendas: Francês, Portuguese (Brazilian), Alemão, Inglês, Espanhol, Japonês...

Habilidades que você terá

Machine LearningGoogle Cloud PlatformFeature EngineeringTensorflowCloud Computing

100% online

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Nível intermediário

Aprox. 11 horas para completar

Sugerido: 1 week of study, 8-12 hours/week...

Inglês

Legendas: Francês, Portuguese (Brazilian), Alemão, Inglês, Espanhol, Japonês...

Programa - O que você aprenderá com este curso

Semana
1
11 minutos para concluir

Welcome to Serverless Machine Learning on Google Cloud Platform

...
2 vídeos ((Total 5 mín.)), 1 teste
2 videos
How to Think About Machine Learning2min
1 exercício prático
Machine Learning Course Pretest6min
3 horas para concluir

Module 1: Getting Started with Machine Learning

...
21 vídeos ((Total 109 mín.)), 1 leitura, 2 testes
21 videos
Types of ML3min
The ML Pipeline2min
Variants of ML model7min
Framing a ML problem2min
Playing with Machine Learning (ML)8min
Optimization9min
A Neural Network Playground18min
Combining Features3min
Feature Engineering3min
Image Models5min
Effective ML2min
What makes a good dataset ?5min
Error Metrics3min
Accuracy2min
Precision and Recall5min
Creating Machine Learning Datasets3min
Splitting Dataset6min
Python Notebooks1min
Create ML Datasets Lab Overview3min
Create ML Datasets Lab Review2min
1 leituras
About Machine Learning10min
1 exercício prático
Module 1 Quiz8min
5 horas para concluir

Module 2: Building ML models with Tensorflow

...
15 vídeos ((Total 65 mín.)), 5 testes
15 videos
What is TensorFlow ?5min
Core TensorFlow5min
Getting Started with TensorFlow Lab Overview7s
TensorFlow Lab Review10min
Estimator API8min
Machine Learning with tf.estimator15s
Estimator Lab Review7min
Building Effective ML6min
Lab Intro: Refactoring to add batching and feature creation38s
Refactoring Lab Review4min
Train and Evaluate4min
Monitoring1min
Lab Intro: Distributed Training and Monitoring2min
Lab Review: Distributed Training and Monitoring7min
1 exercício prático
Module 2 Quiz8min
2 horas para concluir

Module 3: Scaling ML models with Cloud ML Engine

...
7 vídeos ((Total 28 mín.)), 1 leitura, 2 testes
7 videos
Why Cloud ML Engine?6min
Development Workflow1min
Packaging trainer3min
TensorFlow Serving3min
Lab: Scaling up ML39s
Lab Review: Scaling up ML10min
1 leituras
Kubeflow Pipelines10min
1 exercício prático
Module 3 Quiz4min
3 horas para concluir

Module 4: Feature Engineering

...
16 vídeos ((Total 92 mín.)), 2 leituras, 2 testes
16 videos
Good Features7min
Causality8min
Numeric5min
Enough Examples7min
Raw Data to Features1min
Categorical Features8min
Feature Crosses3min
Bucketizing3min
Wide and Deep5min
Where to do Feature Engineering3min
Feature Engineering Lab Overview3min
Feature Engineering Lab Review10min
Hyperparameter Tuning + Demo15min
ML Abstraction Levels4min
Summary1min
2 leituras
ML APIs and Cloud AutoML10min
BigQuery ML10min
1 exercício prático
Module 4 Quiz6min
4.4
231 avaliaçõesChevron Right

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Principais avaliações do Serverless Machine Learning with Tensorflow on Google Cloud Platform

por NPJan 9th 2018

Thank you very much for making this course available on Coursera, I cannot agree more the knowledge of Mr Venkat. This is a great way to help people to get started with Google Machine Learning.

por MGSep 21st 2017

Great course! I've learnt a lot. The concepts where super clear. The coding part was a little difficult, I didn't understand all af it, but it's good to have a complete example to use.

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

  • Sim, você pode assistir uma prévia do primeiro vídeo e ver programa do curso antes de se inscrever. Você precisa comprar o curso para ter acesso ao conteúdo não incluído na prévia.

  • Se decidir se inscrever no curso antes da data de início da sessão, terá acesso a todos os vídeos das palestras e leituras do curso. Também poderá enviar tarefas assim que a sessão começar.

  • Uma vez inscrito, e tão logo sua sessão tenha iniciado, você terá acesso a todos os vídeos e outros recursos, incluindo itens de leitura e fórum de discussão do curso. Você poderá ver e enviar tarefas práticas e concluir tarefas com nota atribuída obrigatórias para obter uma nota e um Certificado de Curso.

  • Se você concluir o curso com êxito, seu Certificado de Curso eletrônico será adicionado à sua página de Participações e você poderá imprimi-lo ou adicioná-lo ao seu perfil no LinkedIn.

  • Este curso é um dos poucos oferecidos pela Coursera que está disponível apenas para alunos que tenham pago ou recebido auxílio financeiro, quando disponível.

  • 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/

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