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BigQuery Machine Learning using Soccer Data

This is a self-paced lab that takes place in the Google Cloud console. Learn how to use BigQuery ML with soccer shot data to create and use an expected goals model.

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What's inside

Syllabus

BigQuery Machine Learning using Soccer Data

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Teaches foundational applied machine learning and data analysis skills that may be used for the prediction of real-world phenomena

Provides a practical hands-on learning experience through self-paced labs, which is highly valuable for learners who want to apply their knowledge immediately

Useful for learners interested in building expected goals models for soccer matches, a skillset that is valuable in the sports analytics industry

Taught by Google Cloud Training, a reputable organization known for its expertise in the field of cloud computing and data analysis

May require learners to have some prior understanding of machine learning concepts and BigQuery, which could be a barrier for beginners

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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 BigQuery Machine Learning using Soccer Data with these activities:

Create a compilation of resources on BigQuery ML

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Contribute to the community by compiling a list of valuable resources on BigQuery ML that can benefit other learners and practitioners.

Browse courses on BigQuery ML

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Gather resources on BigQuery ML
Organize and categorize the resources
Create a shareable document or website

Volunteer at a local data science organization

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Gain practical experience and contribute to the community by volunteering at a local data science organization where you can apply your BigQuery ML skills.

Browse courses on Data Science

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Find a local data science organization
Contact the organization to inquire about volunteering opportunities
Attend volunteer training
Participate in volunteer activities

Follow a tutorial on BigQuery ML for soccer data

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Supplement your understanding of the course material by following a guided tutorial that provides step-by-step instructions on using BigQuery ML with soccer data.

Browse courses on BigQuery ML

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Find a tutorial on BigQuery ML for soccer data
Follow the tutorial step-by-step
Review the concepts covered in the tutorial

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Practice using BigQuery ML with soccer shot data

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Build your skills in using BigQuery ML with real-world soccer data to create and use an expected goals model.

Browse courses on BigQuery ML

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Load the soccer shot data into BigQuery
Create a BigQuery ML model
Train the model
Evaluate the model
Use the model to predict expected goals

Create a presentation on your BigQuery ML model

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Solidify your knowledge by creating a presentation that explains the concepts behind your BigQuery ML model for soccer data and demonstrates its functionality.

Browse courses on BigQuery ML

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Gather your materials
Create your presentation slides
Practice your presentation
Deliver your presentation

Write a blog post about your experience using BigQuery ML

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Expand your understanding by writing a blog post that shares your experiences and insights gained from using BigQuery ML with soccer data.

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Choose a topic for your blog post
Write your blog post
Edit and proofread your blog post
Publish your blog post

Mentor a junior developer on BigQuery ML

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Enhance your understanding of the material while helping others by mentoring a junior developer on how to use BigQuery ML effectively.

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Find a junior developer to mentor
Set up regular mentoring sessions
Provide guidance and support
Track your mentee's progress

Participate in a BigQuery ML competition

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Challenge yourself and test your skills by participating in a BigQuery ML competition where you can showcase your ability to solve real-world problems using BigQuery ML.

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Find a BigQuery ML competition
Register for the competition
Develop your solution
Submit your solution

Career center

Learners who complete BigQuery Machine Learning using Soccer Data will develop knowledge and skills that may be useful to these careers:

Statistician

Statisticians collect, analyze, interpret, and present data. They work in a variety of fields, such as finance, healthcare, and marketing. This course may be useful for those who wish to enter this field as it provides hands-on experience in using BigQuery ML to create and use an expected goals model. This is a valuable skill for Statisticians, who often need to work with large datasets and build models to make predictions and improve decision-making.

See salaries and explore the career path for Statistician

Machine Learning Engineer

Machine Learning Engineers design, build, and maintain machine learning models. They work to ensure that models are accurate, efficient, and scalable. This course may be useful for those who wish to enter this field as it provides hands-on experience in using BigQuery ML to create and use an expected goals model. This is a valuable skill for Machine Learning Engineers, who often need to work with large datasets and build models to solve complex problems.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

Data Scientists use scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. This course may be useful for those who wish to enter this field as it provides hands-on experience in using BigQuery ML to create and use an expected goals model. This is a valuable skill for Data Scientists, who often need to work with large datasets and build models to make predictions and improve decision-making.

See salaries and explore the career path for Data Scientist

Data Architect

Data Architects design and build data architectures for organizations. They work to ensure that data is properly stored, processed, and accessible for analysis. This course may be useful for those who wish to enter this field as it provides hands-on experience in using BigQuery ML to create and use an expected goals model. This is a valuable skill for Data Architects, who often need to work with large datasets and build models to improve data quality and performance.

See salaries and explore the career path for Data Architect

Data Analyst

Data Analysts collect, clean, and analyze data to help businesses make informed decisions. In particular, these professionals prepare and help visualize data through dashboards, reports, presentations, and other methods. They work in a variety of industries and fields, including technology, finance, and healthcare. This course may be useful for those who wish to enter this field as it provides hands-on experience in using BigQuery ML to create and use an expected goals model.

See salaries and explore the career path for Data Analyst

Financial Analyst

Financial Analysts use data to analyze financial performance and make investment recommendations. They work with investors and financial advisors to help them make informed decisions. This course may be useful for those who wish to enter this field as it provides hands-on experience in using BigQuery ML to create and use an expected goals model. This is a valuable skill for Financial Analysts, who often need to work with large datasets and build models to make predictions and improve investment performance.

See salaries and explore the career path for Financial Analyst

Marketing Analyst

Marketing Analysts use data to understand customer behavior and develop marketing campaigns. They work with marketers to track the effectiveness of campaigns and make recommendations for improvement. This course may be useful for those who wish to enter this field as it provides hands-on experience in using BigQuery ML to create and use an expected goals model. This is a valuable skill for Marketing Analysts, who often need to work with large datasets and build models to make predictions and improve campaign performance.

See salaries and explore the career path for Marketing Analyst

Researcher

Researchers conduct original investigations and studies to advance knowledge and understanding in a particular field. They may work in a variety of settings, such as universities, research institutes, and private companies. This course may be useful for those who wish to enter this field as it provides hands-on experience in using BigQuery ML to create and use an expected goals model. This is a valuable skill for Researchers, who often need to collect and analyze data to support their research.

See salaries and explore the career path for Researcher

Business Analyst

Business Analysts use data to identify and solve business problems. They work with stakeholders to understand their needs and develop solutions that meet those needs. This course may be useful for those who wish to enter this field as it provides hands-on experience in using BigQuery ML to create and use an expected goals model. This is a valuable skill for Business Analysts, who often need to work with large datasets and build models to make recommendations and improve decision-making.

See salaries and explore the career path for Business Analyst

Operations Research Analyst

Operations Research Analysts use mathematical and statistical models to solve business problems. They work with businesses to improve efficiency, productivity, and profitability. This course may be useful for those who wish to enter this field as it provides hands-on experience in using BigQuery ML to create and use an expected goals model. This is a valuable skill for Operations Research Analysts, who often need to work with large datasets and build models to make decisions about business operations.

See salaries and explore the career path for Operations Research Analyst

Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze financial data. They develop trading strategies and make investment recommendations. This course may be useful for those who wish to enter this field as it provides hands-on experience in using BigQuery ML to create and use an expected goals model. This is a valuable skill for Quantitative Analysts, who often need to work with large datasets and build models to make predictions and improve decision-making.

See salaries and explore the career path for Quantitative Analyst

Actuary

Actuaries use mathematical and statistical models to assess risk and make financial decisions. They work with insurance companies, pension funds, and other financial institutions. This course may be useful for those who wish to enter this field as it provides hands-on experience in using BigQuery ML to create and use an expected goals model. This is a valuable skill for Actuaries, who often need to work with large datasets and build models to make decisions about risk and financial planning.

See salaries and explore the career path for Actuary

Data Engineer

Data Engineers design, build, and maintain data pipelines and infrastructure. They work to ensure that data is properly stored, processed, and accessible for analysis. This course may be useful for those who wish to enter this field as it provides hands-on experience in using BigQuery ML to create and use an expected goals model. This is a valuable skill for Data Engineers, who often need to work with large datasets and build models to improve data quality and performance.

See salaries and explore the career path for Data Engineer

Product Manager

Product Managers lead the development and launch of new products. They work with engineers, designers, and marketers to ensure that products meet the needs of users. This course may be useful for those who wish to enter this field as it provides hands-on experience in using BigQuery ML to create and use an expected goals model. This is a valuable skill for Product Managers, who often need to work with large datasets and build models to make decisions about product development.

See salaries and explore the career path for Product Manager

Software Engineer

Software Engineers design, develop, and maintain software applications. They work with a variety of programming languages and technologies to create software that meets the needs of users. This course may be useful for those who wish to enter this field as it provides hands-on experience in using BigQuery ML to create and use an expected goals model. This is a valuable skill for Software Engineers, who often need to work with large datasets and build models to improve the performance and functionality of software applications.

See salaries and explore the career path for Software Engineer

Reading list

We've selected seven 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 BigQuery Machine Learning using Soccer Data.

Machine Learning Con Pytorch Y Scikit Lean

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Provides a comprehensive overview of machine learning using Python, including how to use scikit-learn to create and use an expected goals model.

BigQuery Machine Learning using Soccer Data

Two deals to help you save

What's inside

Syllabus

Good to know

Save this course

Activities

Career center

Reading list

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