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Google Cloud Training

Neste curso, vamos definir o que é machine learning e como ele pode beneficiar seu negócio. Você vai conferir algumas demonstrações do ML em ação e aprender termos importantes da área, como instâncias, atributos e rótulos. Nos laboratórios interativos, você vai praticar a invocação de APIs de ML pré-treinadas e criar seus próprios modelos de machine learning usando apenas SQL no BigQuery ML.

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What's inside

Syllabus

Introdução
Informações gerais sobre o conteúdo do curso
Introdução ao machine learning
Neste modelo, vamos definir o que é machine learning e os benefícios que ele pode trazer para seu negócio. Você vai conferir algumas demonstrações do ML em ação e aprender termos importantes da área, como instâncias, atributos e rótulos.
Read more
APIs de ML pré-treinadas
Neste módulo, vamos analisar modelos de ML pré-treinados (como reconhecimento de imagens e análise de sentimento) no Cloud Datalab.
Como criar ​conjuntos de dados de ML no BigQuery
Entender como criar conjuntos de dados de ML com o BigQuery.
Como criar modelos de ML no BigQuery
Neste módulo, você vai aprender a criar modelos de machine learning diretamente no BigQuery. Você vai aprender a usar a nova sintaxe e trabalhar nas fases de criação, avaliação e teste de um modelo de ML.
Recapitulação do curso
Você chegou ao final! Vamos revisar o conteúdo abordado no curso e os recursos disponíveis para continuar o aprendizado.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Ensina conceitos básicos para iniciantes em machine learning e modelagem baseada em SQL no BigQuery
Oferece demonstrações práticas de APIs de ML pré-treinadas, tornando o aprendizado mais envolvente e aplicável
Abrange tópicos relevantes para quem busca conhecimento básico em machine learning e modelagem baseada em SQL

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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 Applying Machine Learning to Your Data with GC - Português with these activities:
Explorar a documentação e tutoriais do BigQuery ML
Seguindo tutoriais e examinando a documentação do BigQuery ML, você pode se familiarizar com os recursos e funcionalidades essenciais da plataforma.
Browse courses on BigQuery ML
Show steps
  • Visite a documentação do BigQuery ML
  • Faça os tutoriais do BigQuery ML no Cloud Datalab
Participar de grupos de estudo ou sessões de prática
Engajar-se com colegas em grupos de estudo ou sessões de prática permitirá que você troque ideias, faça perguntas e fortaleça sua compreensão.
Show steps
  • Encontre ou crie um grupo de estudo
  • Proponha tópicos para discussão e atividades práticas
  • Participe ativamente das sessões, compartilhe seu conhecimento e aprenda com os outros
Criar modelos de ML usando SQL no BigQuery
Praticando a criação de modelos de ML usando SQL diretamente no BigQuery, você reforçará sua compreensão da sintaxe e do processo de desenvolvimento de modelos.
Browse courses on BigQuery ML
Show steps
  • Importe um conjunto de dados de amostra para o BigQuery
  • Crie um modelo de ML usando a sintaxe SQL
  • Teste e avalie seu modelo
Two other activities
Expand to see all activities and additional details
Show all five activities
Compartilhar um projeto de ML do BigQuery
Ao compartilhar um projeto de ML do BigQuery, você pode demonstrar suas habilidades, consolidar seu aprendizado e obter feedback de outros.
Browse courses on BigQuery ML
Show steps
  • Escolha um conjunto de dados e um problema de ML
  • Crie um modelo de ML e treine-o
  • Implemente seu modelo e avalie seu desempenho
  • Compartilhe seu projeto em uma plataforma online ou fórum
Aplicar APIs de ML pré-treinadas em seu próprio projeto
Ao aplicar APIs de ML pré-treinadas em seu próprio projeto, você aplicará os conceitos aprendidos no curso em um contexto prático.
Browse courses on Machine Learning
Show steps
  • Identifique um caso de uso para uma API de ML
  • Integre a API de ML em seu projeto
  • Implemente e teste seu projeto
  • Avalie e refine seu modelo

Career center

Learners who complete Applying Machine Learning to Your Data with GC - Português will develop knowledge and skills that may be useful to these careers:
Statistician
A Statistician collects, analyzes, and interprets data. Those interested in becoming a Statistician may consider taking the course "Applying Machine Learning to Your Data with GC - Portuguese" offered by Google Cloud. This course teaches how to invoke pre-trained ML APIs and create your own ML models using only SQL in BigQuery ML. Note that Statisticians typically need a master's or doctorate degree in statistics or a related field.
Machine Learning Engineer
A Machine Learning Engineer designs, develops, and maintains machine learning models. Those interested in becoming a Machine Learning Engineer may consider taking the course "Applying Machine Learning to Your Data with GC - Portuguese" offered by Google Cloud. This course teaches how to invoke pre-trained ML APIs and create your own ML models using only SQL in BigQuery ML. Note that Machine Learning Engineers typically need a master's or doctorate degree in computer science, engineering, or a related field.
Quantitative Analyst
A Quantitative Analyst uses mathematical and statistical models to analyze data and make predictions. Those interested in becoming a Quantitative Analyst may consider taking the course "Applying Machine Learning to Your Data with GC - Portuguese" offered by Google Cloud. This course teaches how to invoke pre-trained ML APIs and create your own ML models using only SQL in BigQuery ML. Note that Quantitative Analysts typically need a master's or doctorate degree in mathematics, statistics, or a related field.
Actuary
An Actuary uses mathematical and statistical techniques to assess risk. Those interested in becoming an Actuary may consider taking the course "Applying Machine Learning to Your Data with GC - Portuguese" offered by Google Cloud. This course teaches how to invoke pre-trained ML APIs and create your own ML models using only SQL in BigQuery ML. Note that Actuaries typically need a bachelor's degree in mathematics, statistics, or a related field.
Data Scientist
A Data Scientist uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. Those interested in becoming a Data Scientist may consider taking the course "Applying Machine Learning to Your Data with GC - Portuguese" offered by Google Cloud. This course teaches how to invoke pre-trained ML APIs and create your own ML models using only SQL in BigQuery ML. Note that Data Scientists typically need a master's or doctorate degree in a quantitative field or related discipline.
Operations Research Analyst
An Operations Research Analyst uses mathematical and statistical techniques to solve business problems. Those interested in becoming an Operations Research Analyst may consider taking the course "Applying Machine Learning to Your Data with GC - Portuguese" offered by Google Cloud. This course teaches how to invoke pre-trained ML APIs and create your own ML models using only SQL in BigQuery ML. Note that Operations Research Analysts typically need a master's or doctorate degree in operations research, industrial engineering, or a related field.
Data Engineer
A Data Engineer designs, builds, and maintains the infrastructure and processes that store and manage data. Those interested in becoming a Data Engineer may consider taking the course "Applying Machine Learning to Your Data with GC - Portuguese" offered by Google Cloud. This course teaches how to invoke pre-trained ML APIs and create your own ML models using only SQL in BigQuery ML. Note that Data Engineers typically need a bachelor's degree in computer science, data engineering, or a related field.
Risk Manager
A Risk Manager identifies and manages risks. Those interested in becoming a Risk Manager may consider taking the course "Applying Machine Learning to Your Data with GC - Portuguese" offered by Google Cloud. This course teaches how to invoke pre-trained ML APIs and create your own ML models using only SQL in BigQuery ML. Note that Risk Managers typically need a bachelor's degree in finance, risk management, or a related field.
Marketing Manager
A Marketing Manager plans and executes marketing campaigns. Those interested in becoming a Marketing Manager may consider taking the course "Applying Machine Learning to Your Data with GC - Portuguese" offered by Google Cloud. This course teaches how to invoke pre-trained ML APIs and create your own ML models using only SQL in BigQuery ML. Note that Marketing Managers typically need a bachelor's degree in marketing, business administration, or a related field.
Fraud Analyst
A Fraud Analyst investigates and prevents fraud. Those interested in becoming a Fraud Analyst may consider taking the course "Applying Machine Learning to Your Data with GC - Portuguese" offered by Google Cloud. This course teaches how to invoke pre-trained ML APIs and create your own ML models using only SQL in BigQuery ML. Note that Fraud Analysts typically need a bachelor's degree in criminal justice, fraud investigation, or a related field.
Business Analyst
A Business Analyst uses data to identify and solve business problems. Those interested in becoming a Business Analyst may consider taking the course "Applying Machine Learning to Your Data with GC - Portuguese" offered by Google Cloud. This course teaches how to invoke pre-trained ML APIs and create your own ML models using only SQL in BigQuery ML. Note that Business Analysts typically need a bachelor's degree in business administration, economics, or a related field.
Data Architect
A Data Architect designs and builds the infrastructure and processes that store and manage data. Those interested in becoming a Data Architect may consider taking the course "Applying Machine Learning to Your Data with GC - Portuguese" offered by Google Cloud. This course teaches how to invoke pre-trained ML APIs and create your own ML models using only SQL in BigQuery ML. Note that Data Architects typically need a bachelor's degree in computer science, data architecture, or a related field.
Software Engineer
A Software Engineer designs, develops, and maintains software applications. Those interested in becoming a Software Engineer may consider taking the course "Applying Machine Learning to Your Data with GC - Portuguese" offered by Google Cloud. This course teaches how to invoke pre-trained ML APIs and create your own ML models using only SQL in BigQuery ML. Note that Software Engineers typically need a bachelor's degree in computer science, software engineering, or a related field.
Data Analyst
A Data Analyst collects, cleans, and analyzes data to help businesses make informed decisions. Those interested in becoming a Data Analyst may consider taking the course "Applying Machine Learning to Your Data with GC - Portuguese" offered by Google Cloud. This course teaches how to invoke pre-trained ML APIs and create your own ML models using only SQL in BigQuery ML. Note that Data Analysts typically need a bachelor's degree in a quantitative field or related discipline.
Product Manager
A Product Manager plans and manages the development of products. Those interested in becoming a Product Manager may consider taking the course "Applying Machine Learning to Your Data with GC - Portuguese" offered by Google Cloud. This course teaches how to invoke pre-trained ML APIs and create your own ML models using only SQL in BigQuery ML. Note that Product Managers typically need a bachelor's degree in business administration, engineering, or a related field.

Reading list

We've selected nine 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 Applying Machine Learning to Your Data with GC - Português.
Provides a probabilistic perspective on machine learning, covering topics such as Bayesian inference, graphical models, and reinforcement learning.
Covers the practical aspects of implementing machine learning algorithms on big data using Hadoop, Spark, and other distributed computing frameworks.
Provides a practical guide to implementing machine learning algorithms in Python, with a focus on real-world applications.
Provides a gentle introduction to statistical learning, making it accessible to readers with no prior knowledge of the field.

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