How Google does Machine Learning em Português Brasileiro from Coursera

"Quais são as práticas recomendadas para implementar machine learning no Google Cloud? O que é Vertex AI e como é possível usar a plataforma para criar, treinar e implantar modelos de machine learning do AutoML com rapidez e sem escrever nenhuma linha de código? O que é machine learning e que tipos de problema ele pode resolver?

O Google pensa em machine learning de uma forma um pouco diferente. Para nós, o processo de ML é sobre fornecer uma plataforma unificada para conjuntos de dados gerenciados, como uma Feature Store, uma forma de criar, treinar e implantar modelos de machine learning sem escrever nenhuma linha de código. Além disso, o ML também é sobre a habilidade de rotular dados, criar notebooks do Workbench usando frameworks (como TensorFlow, SciKit Learn, Pytorch e R) e muito mais. A plataforma Vertex AI também inclui a possibilidade de treinar modelos personalizados, criar pipelines de componente e realizar previsões em lote e on-line. Também falamos sobre as cinco fases da conversão de um possível caso de uso a ser realizado por machine learning e vemos como é importante não ignorar essas etapas. Finalizamos com um reconhecimento das tendências que o machine learning pode ampliar e como reconhecer isso."

What's inside

Syllabus

Introdução ao curso e à série

Neste módulo, você vai conhecer a série de cursos e os especialistas do Google que vão orientar você nesta jornada.

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Estabelecimentos de ensino e indivíduos interessados em aprender machine learning e buscar se desenvolver no campo

Estabelece uma base sólida para iniciantes e fortalece a base de alunos que já possuem conhecimento intermediário

Desenvolve habilidades profissionais e conhecimentos especializados em machine learning

Oferece uma abordagem abrangente para o estudo de machine learning

Inclui um mix de mídia que contribui para uma experiência de aprendizado envolvente

O curso pertence a uma série, o que indica abrangência e detalhe

Reviews summary

Abordagem do google para machine learning em português

Segundo os alunos, este curso oferece uma introdução útil à abordagem do Google para ML, com foco na plataforma Vertex AI. Eles apreciam a cobertura de tópicos como AutoML, práticas recomendadas de MLOps e IA responsável, considerando estes pontos particularmente valiosos. No entanto, alguns estudantes notam que o curso tende a ser muito alto nível, com falta de profundidade técnica e poucos exemplos práticos ou atividades de codificação. A qualidade da narração e tradução em língua portuguesa é frequentemente elogiada. É mais adequado para quem busca uma visão geral conceitual do que um mergulho técnico profundo.

Narração e texto em português são de qualidade.

"O curso está bem traduzido para o português e a narração é clara e fácil de seguir."

"É ótimo ter um conteúdo de qualidade do Google totalmente em português do Brasil."

"A qualidade do áudio e legendas em português facilita muito o aprendizado de conceitos complexos."

Cobre MLOps e ética em ML de forma útil.

"As aulas sobre práticas recomendadas e IA responsável foram particularmente valiosas para entender a aplicação no mundo real."

"A parte de MLOps e ética em IA é um diferencial e foi bem abordada neste curso."

"Gostei que cobriram aspectos além do modelo, como responsabilidade e processos de ML na prática do Google."

Boa visão geral da plataforma Google Cloud ML.

"Achei a introdução à Vertex AI muito útil, especialmente a parte de AutoML."

"O curso dá uma boa visão geral de como o Google estrutura o ML com a plataforma Vertex AI."

"Entendi melhor o conceito por trás da Vertex AI e suas funcionalidades principais após este curso."

O curso foca mais em conceitos do que em detalhes técnicos.

"O conteúdo é interessante, mas me pareceu um pouco muito alto nível, senti falta de mais profundidade técnica."

"Para quem já tem alguma base, pode ser superficial, esperava mais detalhes práticos e códigos."

"Gostei da visão geral, mas senti que a falta de hands-on limita o aprendizado técnico prático."

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 How Google does Machine Learning em Português Brasileiro with these activities:

Revise Key Concepts from Entry-Level Machine Learning Course

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Review fundamental machine learning concepts such as supervised and unsupervised learning, model evaluation techniques, and common algorithms to reinforce your understanding of the upcoming course material.

Browse courses on Machine Learning Fundamentals

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Go through your notes or textbooks from previous machine learning courses and refresh your understanding of core concepts.
Work through practice problems or online tutorials to test your comprehension.

Explore Beginner-Friendly Vertex AI Tutorials

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Supplement your course learning by following guided tutorials on Vertex AI to gain hands-on experience with its features and capabilities.

Browse courses on Vertex AI

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Identify topics or areas within Vertex AI that you want to explore further.
Search for beginner-level tutorials or documentation on the Google Cloud or Vertex AI websites.
Follow the tutorials step-by-step to create and deploy machine learning models using Vertex AI.

Join a Study Group for Course Support and Collaboration

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Engage with fellow learners to discuss course material, share insights, work on assignments together, and provide mutual support throughout your learning journey.

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Reach out to classmates or online forums to connect with potential study partners.
Establish regular meeting times and decide on a platform for communication.
Prepare for each session by reviewing course materials and identifying discussion topics.

Two other activities

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Create a Mini-Project to Apply Course Concepts to a Real-World Dataset

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Enhance your understanding by applying course concepts to a practical scenario through a mini-project, allowing you to experience the process of data preparation, model training, and evaluation.

Browse courses on Machine Learning Projects

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Identify a small-scale dataset that aligns with your interests.
Define a clear problem statement and determine the machine learning technique you will use.
Create a project on Vertex AI and import your dataset.
Train a model, evaluate its performance, and iterate to improve results.

Connect with a Machine Learning Expert for Personalized Guidance

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Accelerate your learning by seeking guidance from an experienced mentor in the field of machine learning, gaining personalized insights and tailored advice to enhance your understanding and career path.

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Attend industry events, join online forums, and reach out to professionals in your network to identify potential mentors.
Prepare a brief introduction of yourself, your goals, and the areas where you seek guidance.
Respect the time and expertise of your mentor, and schedule regular meetings to discuss your progress and receive feedback.

Career center

Learners who complete How Google does Machine Learning em Português Brasileiro will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

Machine Learning Engineers design, develop, deploy, and maintain machine learning systems. Google's Vertex AI platform is a powerful tool for machine learning engineers, as it provides a unified platform for data management, model training, and deployment. This course will teach you how to use Vertex AI to build and deploy machine learning models, and will help you develop the skills you need to be a successful Machine Learning Engineer.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

Data Scientists use machine learning and other statistical techniques to analyze data and extract insights. Google's Vertex AI platform can help Data Scientists to build and deploy machine learning models, and can also be used to manage and analyze data. This course will teach you how to use Vertex AI to build and deploy machine learning models, and will help you develop the skills you need to be a successful Data Scientist.

See salaries and explore the career path for Data Scientist

Software Engineer

Software Engineers design, develop, and maintain software systems. Machine learning is increasingly being used to power software systems, and Google's Vertex AI platform can help Software Engineers to build and deploy machine learning models. This course will teach you how to use Vertex AI to build and deploy machine learning models, and will help you develop the skills you need to be a successful Software Engineer.

See salaries and explore the career path for Software Engineer

Product Manager

Product Managers are responsible for the development and launch of new products. Machine learning is increasingly being used to create new products and features, and Google's Vertex AI platform can help Product Managers to build and deploy machine learning models. This course will teach you how to use Vertex AI to build and deploy machine learning models, and will help you develop the skills you need to be a successful Product Manager.

See salaries and explore the career path for Product Manager

Data Analyst

Data Analysts use data to identify trends and patterns. Machine learning can be used to automate many of the tasks that Data Analysts perform, and Google's Vertex AI platform can help Data Analysts to build and deploy machine learning models. This course will teach you how to use Vertex AI to build and deploy machine learning models, and will help you develop the skills you need to be a successful Data Analyst.

See salaries and explore the career path for Data Analyst

Business Analyst

Business Analysts use data to solve business problems. Machine learning can be used to automate many of the tasks that Business Analysts perform, and Google's Vertex AI platform can help Business Analysts to build and deploy machine learning models. This course will teach you how to use Vertex AI to build and deploy machine learning models, and will help you develop the skills you need to be a successful Business Analyst.

See salaries and explore the career path for Business Analyst

Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze financial data. Machine learning is increasingly being used to develop new quantitative trading strategies, and Google's Vertex AI platform can help Quantitative Analysts to build and deploy machine learning models. This course will teach you how to use Vertex AI to build and deploy machine learning models, and will help you develop the skills you need to be a successful Quantitative Analyst.

See salaries and explore the career path for Quantitative Analyst

Operations Research Analyst

Operations Research Analysts use mathematical and statistical models to solve business problems. Machine learning is increasingly being used to develop new operations research techniques, and Google's Vertex AI platform can help Operations Research Analysts to build and deploy machine learning models. This course will teach you how to use Vertex AI to build and deploy machine learning models, and will help you develop the skills you need to be a successful Operations Research Analyst.

See salaries and explore the career path for Operations Research Analyst

Market Researcher

Market Researchers use data to understand consumer behavior. Machine learning can be used to automate many of the tasks that Market Researchers perform, and Google's Vertex AI platform can help Market Researchers to build and deploy machine learning models. This course will teach you how to use Vertex AI to build and deploy machine learning models, and will help you develop the skills you need to be a successful Market Researcher.

See salaries and explore the career path for Market Researcher

Risk Analyst

Risk Analysts use data to identify and manage risks. Machine learning is increasingly being used to develop new risk management techniques, and Google's Vertex AI platform can help Risk Analysts to build and deploy machine learning models. This course will teach you how to use Vertex AI to build and deploy machine learning models, and will help you develop the skills you need to be a successful Risk Analyst.

See salaries and explore the career path for Risk Analyst

Statistician

Statisticians use data to analyze and interpret data. Machine learning is increasingly being used to develop new statistical techniques, and Google's Vertex AI platform can help Statisticians to build and deploy machine learning models. This course will teach you how to use Vertex AI to build and deploy machine learning models, and will help you develop the skills you need to be a successful Statistician.

See salaries and explore the career path for Statistician

Financial Analyst

Financial Analysts use data to analyze financial data and make investment recommendations. Machine learning is increasingly being used to develop new financial analysis techniques, and Google's Vertex AI platform can help Financial Analysts to build and deploy machine learning models. This course will teach you how to use Vertex AI to build and deploy machine learning models, and will help you develop the skills you need to be a successful Financial Analyst.

See salaries and explore the career path for Financial Analyst

Actuary

Actuaries use mathematics and statistics to assess and manage risk. Machine learning is increasingly being used to develop new actuarial techniques, and Google's Vertex AI platform can help Actuaries to build and deploy machine learning models. This course will teach you how to use Vertex AI to build and deploy machine learning models, and will help you develop the skills you need to be a successful Actuary.

See salaries and explore the career path for Actuary

Software Developer

Software Developers design, develop, and maintain software systems. Machine learning is increasingly being used to power software systems, and Google's Vertex AI platform can help Software Developers to build and deploy machine learning models. This course will teach you how to use Vertex AI to build and deploy machine learning models, and will help you develop the skills you need to be a successful Software Developer.

See salaries and explore the career path for Software Developer

Data Engineer

Data Engineers design, build, and maintain data systems. Machine learning is increasingly being used to power data systems, and Google's Vertex AI platform can help Data Engineers to build and deploy machine learning models. This course will teach you how to use Vertex AI to build and deploy machine learning models, and will help you develop the skills you need to be a successful Data Engineer.

See salaries and explore the career path for Data Engineer