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

Com a incorporação do machine learning aos pipelines de dados, as empresas podem extrair mais insights. Neste curso, mostramos várias maneiras de incluir o machine learning nos pipelines de dados no Google Cloud Platform, dependendo do nível de personalização necessário. Explicamos como usar o AutoML quando você precisar de pouca ou nenhuma personalização. Para recursos de machine learning mais personalizados, mostramos como usar o AI Platform Notebooks e o BigQuery Machine Learning. Também explicamos como produzir soluções de machine learning usando o Kubeflow. Além disso, haverá atividades práticas de criação de modelos de ML no Google Cloud Platform usando o QwikLabs.

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What's inside

Syllabus

Introdução

Neste módulo, apresentamos o curso e a programação.

Introdução ao Analytics e à IA

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

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Indicado para quem busca incluir machine learning nos pipelines de dados, com opções para personalização de acordo com o nível de necessidade

Aborda desde opções de APIs de modelos pré-criados até a criação de modelos personalizados com SQL e AutoML

Oferece atividades práticas no Google Cloud Platform por meio do QwikLabs

Apresenta o Kubeflow, uma plataforma de orquestração de machine learning

Exige conhecimento prévio em machine learning e pipelines de dados

Não oferece certificação após a conclusão do curso

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Reviews summary

Análise, ml e ia no gcp: visão prática

Segundo os alunos, este curso oferece uma visão abrangente e prática sobre como aplicar Machine Learning e IA no Google Cloud Platform. Muitos destacam que os laboratórios práticos no QwikLabs são um diferencial positivo, ajudando a fixar o conteúdo e a entender a aplicabilidade real das ferramentas como AutoML, BigQuery ML e Kubeflow. É considerado um excelente ponto de partida para profissionais e estudantes com alguma base em dados, sendo muito relevante para o mercado de trabalho. Embora o ritmo possa ser acelerado para alguns, e exija estudo adicional para aprofundamento, a didática do instrutor e a organização dos módulos são geralmente bem avaliadas.

Conteúdo altamente aplicável ao mercado de trabalho e para migração ao GCP.

"O conteúdo é muito relevante e atualizado, útil para quem usa BigQuery ML no dia a dia."

"É um ótimo ponto de partida para quem já tem alguma familiaridade com data science e quer migrar para GCP."

"Fiquei muito satisfeito com o aprendizado e como isso se aplica ao meu trabalho."

O curso oferece uma boa visão geral de várias ferramentas de ML/IA no GCP.

"Gostei bastante, o curso cobre uma boa variedade de tópicos, desde AutoML até Kubeflow."

"É um panorama sólido sobre o ecossistema de ML no GCP. Cobriu o essencial."

"A abrangência de tópicos como AutoML, BigQuery ML e Kubeflow é fantástica e relevante."

Os laboratórios do QwikLabs são muito eficazes para o aprendizado prático.

"Os laboratórios no QwikLabs são muito práticos e ajudam a fixar o conteúdo."

"Para mim, os labs do QwikLabs são a melhor parte, são super úteis e um diferencial."

"Gostei muito dos exercícios, eles me permitiram aplicar o que aprendi imediatamente."

Houve menções isoladas sobre a qualidade da produção e tradução do curso.

"Achei a qualidade da produção um pouco inferior. Parecia que o conteúdo era uma tradução literal e perdia um pouco da clareza."

O ritmo acelerado exige dedicação e aprofundamento extra em alguns conceitos.

"Senti que o ritmo é um pouco acelerado para iniciantes, precisei de tempo extra para absorver."

"Achei o curso um pouco superficial em certas áreas; as explicações às vezes são rápidas demais."

"Senti falta de um aprofundamento maior em alguns conceitos; precisei complementar com outras fontes."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Smart Analytics, Machine Learning, and AI on GCP em Português Brasileiro with these activities:

Aprenda sobre as melhores práticas para construir pipelines de dados com o Google Cloud Platform

Show steps

Aprimore suas habilidades seguindo tutoriais sobre as melhores práticas para a construção de pipelines de dados usando o Google Cloud Platform.

Browse courses on Google Cloud Platform

Show steps

Encontre um tutorial sobre melhores práticas para pipelines de dados com o Google Cloud Platform.
Siga as etapas do tutorial.
Aplique as práticas aprendidas em seus próprios projetos.

Exercite os conceitos praticando a criação de pipelines de dados usando o Google Cloud Platform

Show steps

Fortaleça sua compreensão dos conceitos praticando a construção de pipelines de dados usando a plataforma do Google Cloud.

Browse courses on Google Cloud Platform

Show steps

Crie um novo pipeline de dados no Google Cloud Platform.
Adicione fontes de dados ao seu pipeline.
Transforme e limpe seus dados.
Treine e avalie um modelo de machine learning.
Implante seu modelo em produção.

Participe de workshops ou webinars sobre pipelines de dados

Show steps

Amplie seus conhecimentos participando de workshops ou webinars conduzidos por especialistas em pipelines de dados.

Show steps

Pesquise workshops ou webinars sobre pipelines de dados.
Inscreva-se e participe do workshop ou webinar.
Faça anotações e faça perguntas durante o workshop ou webinar.

One other activity

Expand to see all activities and additional details

Show all four activities

Construa um projeto de pipeline de dados do zero usando o Google Cloud Platform

Show steps

Aprofunde sua compreensão construindo um projeto de pipeline de dados completo usando a plataforma do Google Cloud.

Browse courses on Google Cloud Platform

Show steps

Crie um novo projeto no Google Cloud Platform.
Defina o escopo e os objetivos do seu projeto.
Construa um pipeline de dados que atenda aos requisitos do seu projeto.
Implante seu pipeline de dados em produção.
Monitore e avalie o desempenho do seu pipeline de dados.

Career center

Learners who complete Smart Analytics, Machine Learning, and AI on GCP em Português Brasileiro will develop knowledge and skills that may be useful to these careers:

Data Scientist

A Data Scientist applies scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data. This course would be very helpful for someone wanting to enter this field, as it provides the opportunity to gain hands-on experience with Google Cloud Platform's machine learning and AI tools, such as AutoML, AI Platform Notebooks, and BigQuery Machine Learning. This will provide a valuable foundation for a future Data Scientist, and help them stay competitive in the job market.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

A Machine Learning Engineer designs, develops, and maintains machine learning models and applications. This course provides a good foundation for a career as a Machine Learning Engineer, as it introduces learners to the Google Cloud Platform's machine learning and AI tools and how to use them to create and deploy machine learning solutions. The course also covers topics such as data preparation, model building, and model evaluation, which are essential skills for a Machine Learning Engineer.

See salaries and explore the career path for Machine Learning Engineer

Data Analyst

A Data Analyst collects, analyzes, and interprets data in order to identify trends, patterns, and insights. This course would be helpful for someone wanting to become a Data Analyst, as it helps demonstrate how to use Google Cloud Platform's machine learning and AI tools to extract insights from data. The course also covers topics such as data visualization and data mining, which are essential skills for a Data Analyst.

See salaries and explore the career path for Data Analyst

AI Engineer

An AI Engineer designs, develops, and maintains AI systems. This course would be helpful for someone wanting to become an AI Engineer, as it introduces learners to the Google Cloud Platform's machine learning and AI tools and how to use them to create and deploy AI solutions. The course also covers topics such as AI principles, AI development, and AI deployment, which are essential skills for an AI Engineer.

See salaries and explore the career path for AI Engineer

Software Engineer

A Software Engineer designs, develops, and maintains software systems. This course may be helpful for someone wanting to become a Software Engineer, as it provides the opportunity to gain hands-on experience with Google Cloud Platform's machine learning and AI tools. This will provide a valuable foundation for a future Software Engineer, and help them stay competitive in the job market.

See salaries and explore the career path for Software Engineer

Business Analyst

A Business Analyst analyzes business processes and identifies areas for improvement. This course may be helpful for someone wanting to become a Business Analyst, as it provides the opportunity to gain hands-on experience with Google Cloud Platform's machine learning and AI tools. This will help a future Business Analyst stay competitive in the job market, as machine learning and AI are becoming increasingly important in business.

See salaries and explore the career path for Business Analyst

Project Manager

A Project Manager plans, executes, and closes projects. This course may be helpful for someone wanting to become a Project Manager, as it provides the opportunity to gain hands-on experience with Google Cloud Platform's machine learning and AI tools. This will help a future Project Manager stay competitive in the job market, as machine learning and AI are becoming increasingly important in project management.

See salaries and explore the career path for Project Manager

Data Architect

A Data Architect designs and builds data architectures. This course may be helpful for someone wanting to become a Data Architect, as it provides the opportunity to gain hands-on experience with Google Cloud Platform's machine learning and AI tools. This will help a future Data Architect stay competitive in the job market, as machine learning and AI are becoming increasingly important in data architecture.

See salaries and explore the career path for Data Architect

Database Administrator

A Database Administrator maintains and manages databases. This course may be helpful for someone wanting to become a Database Administrator, as it provides the opportunity to gain hands-on experience with Google Cloud Platform's machine learning and AI tools. This will help a future Database Administrator stay competitive in the job market, as machine learning and AI are becoming increasingly important in database management.

See salaries and explore the career path for Database Administrator

Business Intelligence Analyst

A Business Intelligence Analyst analyzes data and provides insights to businesses. This course may be helpful for someone wanting to become a Business Intelligence Analyst, as it provides the opportunity to gain hands-on experience with Google Cloud Platform's machine learning and AI tools. This will help a future Business Intelligence Analyst stay competitive in the job market, as machine learning and AI are becoming increasingly important in business intelligence.

See salaries and explore the career path for Business Intelligence Analyst

Data Engineer

A Data Engineer designs and builds data pipelines. This course may be helpful for someone wanting to become a Data Engineer, as it provides the opportunity to gain hands-on experience with Google Cloud Platform's machine learning and AI tools. This will help a future Data Engineer stay competitive in the job market, as machine learning and AI are becoming increasingly important in data engineering.

See salaries and explore the career path for Data Engineer

Product Manager

A Product Manager develops and manages products. This course may be helpful for someone wanting to become a Product Manager, as it provides the opportunity to gain hands-on experience with Google Cloud Platform's machine learning and AI tools. This will help a future Product Manager stay competitive in the job market, as machine learning and AI are becoming increasingly important in product management.

See salaries and explore the career path for Product Manager

Quantitative Analyst

A Quantitative Analyst analyzes data and develops models to make investment decisions. This course may be helpful for someone wanting to become a Quantitative Analyst, as it provides the opportunity to gain hands-on experience with Google Cloud Platform's machine learning and AI tools. This will help a future Quantitative Analyst stay competitive in the job market, as machine learning and AI are becoming increasingly important in quantitative analysis.

See salaries and explore the career path for Quantitative Analyst

Consultant

A Consultant provides advice and guidance to clients. This course may be helpful for someone wanting to become a Consultant, as it provides the opportunity to gain hands-on experience with Google Cloud Platform's machine learning and AI tools. This will help a future Consultant stay competitive in the job market, as machine learning and AI are becoming increasingly important in consulting.

See salaries and explore the career path for Consultant

Researcher

A Researcher conducts research and develops new knowledge. This course may be helpful for someone wanting to become a Researcher, as it provides the opportunity to gain hands-on experience with Google Cloud Platform's machine learning and AI tools. This will help a future Researcher stay competitive in the job market, as machine learning and AI are becoming increasingly important in research.

See salaries and explore the career path for Researcher

Reading list

We've selected ten books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Smart Analytics, Machine Learning, and AI on GCP em Português Brasileiro.

Inteligência Artificial - Uma Abordagem Moderna

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Aborda os princípios fundamentais da inteligência artificial, oferecendo uma visão geral abrangente do campo.

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

Here's a deal for you

What's inside

Syllabus

Traffic lights

Save this course

Reviews summary

Análise, ml e ia no gcp: visão prática

Activities

Career center

Reading list

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