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Google Cloud Training

This is a self-paced lab that takes place in the Google Cloud console. In this lab, you'll learn how to use BigQuery to create machine learning models for datasets to create a model that predicts whether a visitor will make a transaction.

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What's inside

Syllabus

Getting Started with BigQuery Machine Learning
In this lab you'll learn how to use BigQuery to create machine learning models for datasets to create a model that predicts whether a visitor will make a transaction.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops skills for creating machine learning models for datasets, which are core skills for data scientists and machine learning engineers
Self-paced and hands-on labs allow learners to practice and apply their knowledge immediately
Taught by Google Cloud Training, recognized for their expertise in cloud computing and machine learning
Provides a strong foundation for beginners in machine learning
May require prior knowledge of BigQuery and machine learning concepts

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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 Getting Started with BigQuery Machine Learning with these activities:
Review linear algebra and calculus
Refresh foundational math skills to strengthen understanding of machine learning algorithms.
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  • Review linear algebra concepts
  • Review calculus concepts
Review machine learning fundamentals
Refresh knowledge of machine learning concepts to enhance understanding of BigQuery Machine Learning.
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  • Review supervised and unsupervised learning
  • Review common machine learning algorithms
Review Google Cloud Machine Learning documentation
Review Google Cloud documentation to deepen understanding of machine learning concepts and BigQuery specifically.
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  • Identify relevant documentation for BigQuery Machine Learning
  • Read and understand the documentation
  • Apply concepts learned to practice exercises
Five other activities
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Show all eight activities
Discuss machine learning concepts with peers
Engage with peers to solidify understanding of machine learning concepts and share knowledge.
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  • Find peers interested in discussing machine learning
  • Schedule a discussion session
  • Discuss machine learning concepts and share knowledge
Practice creating machine learning models in BigQuery
Complete practice drills to solidify understanding of creating machine learning models in BigQuery.
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  • Follow the steps in the Google Cloud Training lab
  • Create a machine learning model in BigQuery
  • Evaluate the performance of the model
Create a collection of resources on BigQuery Machine Learning
Contribute to the learning community by compiling resources that can benefit others.
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  • Gather resources on BigQuery Machine Learning
  • Organize and categorize the resources
  • Share the collection with others
Build a machine learning model to predict customer churn
Create a deliverable that demonstrates application of machine learning concepts to a real-world problem.
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  • Gather data on customer churn
  • Create a machine learning model to predict churn
  • Evaluate the performance of the model
  • Deploy the model to production
Build a web application that uses BigQuery Machine Learning
Challenge yourself by building a project that integrates real-world application with machine learning concepts.
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  • Design the web application
  • Implement the machine learning model
  • Deploy the web application

Career center

Learners who complete Getting Started with BigQuery Machine Learning will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineers design, build, and deploy machine learning models. This course in BigQuery Machine Learning can help Machine Learning Engineers develop the skills needed to create and deploy machine learning models that can be used to solve a variety of business problems.
Data Architect
Data Architects design and manage the data architecture of an organization. This course in BigQuery Machine Learning can help Data Architects develop the skills needed to create and manage data architectures that are scalable, reliable, and secure.
Data Scientist
Data Scientists use their skills in machine learning, statistics, and data analysis to solve complex business problems. This course in BigQuery Machine Learning can help Data Scientists develop the skills needed to create and deploy machine learning models that can be used to predict customer behavior, identify fraud, and optimize business processes.
Data Analyst
Data Analysts use their skills in data analysis and visualization to help businesses understand their data and make better decisions. This course in BigQuery Machine Learning can help Data Analysts build a strong foundation in machine learning and develop the skills needed to create and deploy predictive models that can be used to solve business problems.
Data Engineer
Data Engineers design, build, and maintain the data infrastructure that businesses need to store, process, and analyze their data. This course in BigQuery Machine Learning can help Data Engineers develop the skills needed to create and manage machine learning models that can be used to automate data processing tasks and improve the efficiency of data analysis.
Business Analyst
Business Analysts use their knowledge of data and technology to solve business problems and improve decision-making. This course in BigQuery Machine Learning may assist Business Analysts in developing the skills needed to analyze large datasets and create predictive models that can be used to identify trends, forecast demand, and make better informed decisions.
Operations Research Analyst
Operations Research Analysts use their skills in mathematics, statistics, and computer programming to solve complex problems in business and industry. This course in BigQuery Machine Learning can help Operations Research Analysts develop the skills needed to create and use machine learning models to optimize operations and improve decision-making.
Statistician
Statisticians use their skills in mathematics, statistics, and data analysis to solve problems in a variety of fields. This course in BigQuery Machine Learning may be useful for Statisticians who want to develop a deeper understanding of how machine learning can be used to improve statistical analysis.
Product Manager
Product Managers are responsible for the planning, development, and launch of new products and services. This course in BigQuery Machine Learning may be useful for Product Managers who want to develop a deeper understanding of how machine learning can be used to improve product development and marketing.
Systems Analyst
Systems Analysts use their skills in business analysis and technology to design and implement computer systems. This course in BigQuery Machine Learning may be useful for Systems Analysts who want to develop a deeper understanding of how machine learning can be used to improve systems design and implementation.
Software Engineer
Software Engineers design, develop, and maintain software applications. This course in BigQuery Machine Learning may be useful for Software Engineers who want to develop a deeper understanding of how machine learning can be used to improve software development.
Web Developer
Web Developers create and maintain websites and web applications. This course in BigQuery Machine Learning may be useful for Web Developers who want to develop a deeper understanding of how machine learning can be used to improve website and web application development.
User Experience (UX) Designer
User Experience Designers create products and services that are easy to use and enjoyable to interact with. This course in BigQuery Machine Learning may be useful for User Experience Designers who want to develop a deeper understanding of how machine learning can be used to improve user experience.
Technical Writer
Technical Writers create documentation that explains complex technical concepts to a variety of audiences. This course in BigQuery Machine Learning may be useful for Technical Writers who want to develop a deeper understanding of how machine learning can be used to improve technical documentation.
Project Manager
Project Managers are responsible for planning, executing, and closing projects. This course in BigQuery Machine Learning may be useful for Project Managers who want to develop a deeper understanding of how machine learning can be used to improve project management.

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 Getting Started with BigQuery Machine Learning.
Provides a comprehensive overview of machine learning with Python. It covers a wide range of topics, including data preparation, model selection, and model evaluation. It great resource for anyone who wants to learn more about using Python for machine learning.
Provides a practical guide to using Hadoop for big data analytics. It covers a wide range of topics, including data storage, data processing, and data analysis. It valuable resource for anyone who wants to learn more about using Hadoop for big data analytics.
Provides a practical guide to using R for big data analytics. It covers a wide range of topics, including data storage, data processing, and data analysis. It valuable resource for anyone who wants to learn more about using R for big data analytics.
Provides a practical guide to big data analytics. It covers a wide range of topics, including data collection, data storage, and data analysis. It valuable resource for anyone who wants to learn more about big data analytics.
Provides a practical guide to data science for business. It covers a wide range of topics, including data collection, data analysis, and data visualization. It valuable resource for anyone who wants to learn more about using data science for business.
Provides a practical introduction to machine learning. It covers a wide range of topics, including data preparation, model selection, and model evaluation. It great resource for anyone who wants to learn more about machine learning.
Provides a hands-on introduction to machine learning. It covers a wide range of topics, including data preparation, model selection, and model evaluation. It great resource for anyone who wants to learn more about machine learning.
Provides a gentle introduction to machine learning. It covers a wide range of topics, including data preparation, model selection, and model evaluation. It great resource for anyone who wants to learn more about machine learning.
Provides a friendly introduction to machine learning. It covers a wide range of topics, including data preparation, model selection, and model evaluation. It great resource for anyone who wants to learn more about machine learning.

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