We may earn an affiliate commission when you visit our partners.
BigQuery Machine Learning using Soccer Data
Google Cloud Training
Google Cloud Training
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.
Register for this course and see more details by visiting:
OpenCourser.com/course/2zbn0x/bigquery
What's inside
Syllabus
BigQuery Machine Learning using Soccer Data
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
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
Save this course
Save BigQuery Machine Learning using Soccer Data to your list so you can find it easily later:
Save
Save
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
Show steps
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
Show steps
-
Gather resources on BigQuery ML
-
Organize and categorize the resources
-
Create a shareable document or website
Volunteer at a local data science organization
Show steps
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
Show steps
-
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
Show steps
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
Show steps
-
Find a tutorial on BigQuery ML for soccer data
-
Follow the tutorial step-by-step
-
Review the concepts covered in the tutorial
Five other activities
Expand to see all activities and additional details
Show all eight activities
Practice using BigQuery ML with soccer shot data
Show steps
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
Show steps
-
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
Show steps
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
Show steps
-
Gather your materials
-
Create your presentation slides
-
Practice your presentation
-
Deliver your presentation
Write a blog post about your experience using BigQuery ML
Show steps
Expand your understanding by writing a blog post that shares your experiences and insights gained from using BigQuery ML with soccer data.
Browse courses on
BigQuery ML
Show steps
-
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
Show steps
Enhance your understanding of the material while helping others by mentoring a junior developer on how to use BigQuery ML effectively.
Browse courses on
BigQuery ML
Show steps
-
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
Show steps
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.
Browse courses on
BigQuery ML
Show steps
-
Find a BigQuery ML competition
-
Register for the competition
-
Develop your solution
-
Submit your solution
Create a compilation of resources on BigQuery ML
Show steps
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
Show steps
Show steps
Show steps
- Gather resources on BigQuery ML
- Organize and categorize the resources
- Create a shareable document or website
Volunteer at a local data science organization
Show steps
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
Show steps
Show steps
Show steps
- 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
Show steps
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
Show steps
Show steps
Show steps
- Find a tutorial on BigQuery ML for soccer data
- Follow the tutorial step-by-step
- Review the concepts covered in the tutorial
Five other activities
Expand to see all activities and additional details
Show all eight activities
Practice using BigQuery ML with soccer shot data
Show steps
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
Show steps
Show steps
Show steps
- 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
Show steps
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
Show steps
Show steps
Show steps
- Gather your materials
- Create your presentation slides
- Practice your presentation
- Deliver your presentation
Write a blog post about your experience using BigQuery ML
Show steps
Expand your understanding by writing a blog post that shares your experiences and insights gained from using BigQuery ML with soccer data.
Browse courses on
BigQuery ML
Show steps
Show steps
Show steps
- 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
Show steps
Enhance your understanding of the material while helping others by mentoring a junior developer on how to use BigQuery ML effectively.
Browse courses on
BigQuery ML
Show steps
Show steps
Show steps
- 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
Show steps
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.
Browse courses on
BigQuery ML
Show steps
Show steps
Show steps
- 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
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.
Machine Learning Engineer
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.
Data Scientist
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.
Data Architect
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.
Data Analyst
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.
Financial 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.
Marketing 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.
Researcher
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.
Business Analyst
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.
Operations Research 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.
Quantitative 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.
Actuary
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.
Data Engineer
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.
Product Manager
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.
Software Engineer
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.
For more career information including salaries, visit:
OpenCourser.com/course/2zbn0x/bigquery
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.
Provides a comprehensive overview of machine learning using Python, including how to use scikit-learn to create and use an expected goals model.
Provides a comprehensive overview of the history of soccer.
Provides a comprehensive overview of the tactics of soccer.
Provides a comprehensive overview of the training of soccer players.
Provides a comprehensive overview of the world of soccer.
Save
Provides a comprehensive overview of the history of soccer.
Save
Provides a comprehensive overview of the game of soccer.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/2zbn0x/bigquery
Share
Similar courses
Here are nine courses similar to
BigQuery Machine Learning using Soccer Data.
Introduction to Javascript
OpenCourser.com/course/xgghwq/introduction
Introduction to Javascript
Less relevant
EF Core 6: Cross-platform Development
OpenCourser.com/course/m7ftbt/ef
EF Core 6: Cross-platform Development
Less relevant
Proxy Objects and Reflect in JavaScript
OpenCourser.com/course/po5tmj/proxy
Proxy Objects and Reflect in JavaScript
Less relevant
Introduction to Microsoft Excel
OpenCourser.com/course/izj5lm/introduction
Introduction to Microsoft Excel
Less relevant
Everyday PowerShell for Developers on Linux, macOS, and Windows
OpenCourser.com/course/lm3wf2/everyday
Everyday PowerShell for Developers on Linux, macOS, and...
Less relevant
Deliver No-Code/Low-Code Products that Delight Customers and Stakeholders – Product Development and Management Skills.
OpenCourser.com/course/n0zxdq/deliver
Deliver No-Code/Low-Code Products that Delight Customers...
Less relevant
Advanced Creative Thinking and AI: Tools for Success
OpenCourser.com/course/1q01nf/advanced
Advanced Creative Thinking and AI: Tools for Success
Less relevant
Writing Zeek Rules and Scripts
OpenCourser.com/course/o6o15e/writing
Writing Zeek Rules and Scripts
Less relevant
Go 1: Using Range With Slices (Interactive)
OpenCourser.com/course/e12hmk/go
Go 1: Using Range With Slices (Interactive)
Less relevant
Effort
45 minutes
Level
Intermediate
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
English
Good to know
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
Our mission
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
Affiliate disclosure
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.
© 2016 - 2024 OpenCourser