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Google Cloud Training
This is a self-paced lab that takes place in the Google Cloud console.
Read more
This is a self-paced lab that takes place in the Google Cloud console.
Read more
This is a self-paced lab that takes place in the Google Cloud console.
Use BigQuery to explore the NCAA dataset of basketball games, teams, and players. The data covers plays from 2009 and scores from 1996. Watch How the NCAA is using Google Cloud to tap into decades of sports data.
Register for this course and see more details by visiting:
OpenCourser.com/course/rnwwa2/exploring
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What's inside
Syllabus
Exploring NCAA Data with BigQuery
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Teaches how to use BigQuery to explore sports data
Uses a self-paced lab that takes place in the Google Cloud console
Instructors are Google Cloud Training, who has expertise in teaching cloud computing concepts
Provides an opportunity to explore the NCAA dataset of basketball games, teams, and players
Save this course
Save Exploring NCAA Data with BigQuery to your list so you can find it easily later:
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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 Exploring NCAA Data with BigQuery with these
activities:
Run a few basic SQL queries
Show steps
Refresh your SQL skills before taking this course to clear prerequisites and better help you prepare for success when the course finally begins.
Browse courses on
SQL
Show steps
-
Connect to a database management system.
-
Create a table with a few columns.
-
Insert some data into the table.
-
Select data from the table using simple WHERE clauses.
Watch a video tutorial or read an article about BigQuery
Show steps
Reviewing past coursework or study materials can help refresh knowledge in advance of taking a course.
Browse courses on
BigQuery
Show steps
-
Search for a video tutorial or article about BigQuery.
-
Watch or read the tutorial.
Complete the Google BigQuery Standard SQL tutorial
Show steps
Following a tutorial can help refine existing SQL skills or develop new ones.
Browse courses on
SQL
Show steps
-
Visit the Google BigQuery Standard SQL tutorial page.
-
Read through the tutorial.
-
Follow the instructions to complete the exercises.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Practice writing SQL queries on the NCAA dataset
Show steps
Repetitive exercises can reinforce understanding and refine skills.
Browse courses on
SQL
Show steps
-
Familiarize yourself with the NCAA dataset schema.
-
Write a few simple queries to retrieve data from the NCAA dataset.
-
Challenge yourself by writing more complex queries.
Attend a study group or join an online forum to discuss the course material
Show steps
Peer practice sessions or study groups can add color to the materials covered in this course.
Show steps
-
Find a study group or online forum that focuses on this course or BigQuery.
-
Attend the study group or participate in the online forum regularly.
-
Ask questions, share your insights, and collaborate with other learners.
Create a data visualization of the NCAA dataset
Show steps
Creating a data visualization can help solidify learning and expand on a part of the course.
Browse courses on
Data Visualization
Show steps
-
Choose a data visualization tool.
-
Connect the tool to the NCAA dataset.
-
Create a visualization that represents the data in a meaningful way.
Compile your notes, assignments, and quizzes into a single document
Show steps
Organizing, expanding on, and reviewing notes, assignments, quizzes, and exams can improve retention and deepen knowledge.
Show steps
-
Gather all of your notes, assignments, and quizzes from this course.
-
Organize the materials in a logical order.
-
Review the materials regularly.
Contribute to a BigQuery open-source project
Show steps
Participating in open-source projects can contribute to the learning process by exposing you to real-world challenges and allowing you to learn from others.
Browse courses on
BigQuery
Show steps
-
Find a BigQuery open-source project that you are interested in.
-
Submit a pull request with your contribution.
Run a few basic SQL queries
Show steps
Refresh your SQL skills before taking this course to clear prerequisites and better help you prepare for success when the course finally begins.
Browse courses on
SQL
Show steps
Show steps
Show steps
- Connect to a database management system.
- Create a table with a few columns.
- Insert some data into the table.
- Select data from the table using simple WHERE clauses.
Watch a video tutorial or read an article about BigQuery
Show steps
Reviewing past coursework or study materials can help refresh knowledge in advance of taking a course.
Browse courses on
BigQuery
Show steps
Show steps
Show steps
- Search for a video tutorial or article about BigQuery.
- Watch or read the tutorial.
Complete the Google BigQuery Standard SQL tutorial
Show steps
Following a tutorial can help refine existing SQL skills or develop new ones.
Browse courses on
SQL
Show steps
Show steps
Show steps
- Visit the Google BigQuery Standard SQL tutorial page.
- Read through the tutorial.
- Follow the instructions to complete the exercises.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Practice writing SQL queries on the NCAA dataset
Show steps
Repetitive exercises can reinforce understanding and refine skills.
Browse courses on
SQL
Show steps
Show steps
Show steps
- Familiarize yourself with the NCAA dataset schema.
- Write a few simple queries to retrieve data from the NCAA dataset.
- Challenge yourself by writing more complex queries.
Attend a study group or join an online forum to discuss the course material
Show steps
Peer practice sessions or study groups can add color to the materials covered in this course.
Show steps
Show steps
Show steps
- Find a study group or online forum that focuses on this course or BigQuery.
- Attend the study group or participate in the online forum regularly.
- Ask questions, share your insights, and collaborate with other learners.
Create a data visualization of the NCAA dataset
Show steps
Creating a data visualization can help solidify learning and expand on a part of the course.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Choose a data visualization tool.
- Connect the tool to the NCAA dataset.
- Create a visualization that represents the data in a meaningful way.
Compile your notes, assignments, and quizzes into a single document
Show steps
Organizing, expanding on, and reviewing notes, assignments, quizzes, and exams can improve retention and deepen knowledge.
Show steps
Show steps
Show steps
- Gather all of your notes, assignments, and quizzes from this course.
- Organize the materials in a logical order.
- Review the materials regularly.
Contribute to a BigQuery open-source project
Show steps
Participating in open-source projects can contribute to the learning process by exposing you to real-world challenges and allowing you to learn from others.
Browse courses on
BigQuery
Show steps
Show steps
Show steps
- Find a BigQuery open-source project that you are interested in.
- Submit a pull request with your contribution.
Career center
Learners who complete Exploring NCAA Data with BigQuery will develop knowledge and skills
that may be useful to these careers:
Sports Data Scientist
Sports Data Scientist
Sports Data Scientists use data to build models and solve problems in the sports industry. This course may be particularly relevant for aspiring Sports Data Scientists because it provides hands-on experience with BigQuery, a tool that is used by many sports organizations to store and analyze data.
Sports Data Engineer
Sports Data Engineer
Sports Data Engineers design and build systems for storing, processing, and analyzing sports data. This course may be particularly relevant for aspiring Sports Data Engineers because it provides hands-on experience with BigQuery, a tool that is used by many sports organizations to store and analyze data.
Sports Data Analyst
Sports Data Analyst
Sports Data Analysts use data to analyze sports performance and make predictions. This course may be particularly relevant for aspiring Sports Data Analysts because it provides hands-on experience with BigQuery, a tool that is used by many sports organizations to store and analyze data.
Statistician
Statistician
Statisticians collect, analyze, and interpret data. This course may be useful for aspiring Statisticians because it provides hands-on experience with BigQuery, a tool that can be used to store and analyze large datasets.
Data Visualization Analyst
Data Visualization Analyst
Data Visualization Analysts create visualizations that help people understand data. This course may be useful for aspiring Data Visualization Analysts because it provides hands-on experience with BigQuery, a tool that can be used to store and analyze large datasets.
Business Analyst
Business Analyst
Business Analysts help businesses make better decisions by analyzing data and understanding business needs. This course may be useful for aspiring Business Analysts because it provides hands-on experience with BigQuery, a tool that can be used to store and analyze large datasets.
Database Administrator
Database Administrator
Database Administrators design and maintain databases. This course may be useful for aspiring Database Administrators because it provides hands-on experience with BigQuery, a cloud-based data warehouse.
Product Manager, Data
Product Manager, Data
Product Managers, Data manage data products and ensure that they meet the needs of users. This course may be useful for aspiring Product Managers, Data because it provides hands-on experience with BigQuery, a cloud-based data warehouse that is used by many large organizations.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design and build systems that can learn from data and make predictions. This course may be useful for aspiring Machine Learning Engineers because it provides hands-on experience with BigQuery, a tool that can be used to store and analyze large datasets.
Software Engineer, Data
Software Engineer, Data
Software Engineers, Data build systems for storing, processing, and analyzing data. This course may be useful for aspiring Software Engineers, Data because it provides hands-on experience with BigQuery, a cloud-based data warehouse that is used by many large organizations.
Data Architect
Data Architect
Data Architects design and build data systems. This course may be useful for aspiring Data Architects because it provides hands-on experience with BigQuery, a cloud-based data warehouse that is used by many large organizations.
Data Scientist
Data Scientist
Data Scientists use data to build models and solve problems. This course may be useful for aspiring Data Scientists because it provides hands-on experience with BigQuery, a tool that can be used to store and analyze large datasets.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze data and make predictions. This course may be useful for aspiring Quantitative Analysts because it provides hands-on experience with BigQuery, a tool that can be used to store and analyze large datasets.
Data Engineer
Data Engineer
Data Engineers design and build systems for storing, processing, and analyzing data. This course may be useful for aspiring Data Engineers because it provides hands-on experience with BigQuery, a cloud-based data warehouse that is used by many large organizations.
Data Analyst
Data Analyst
Data Analysts help businesses make better decisions by collecting, analyzing, and interpreting data. This course may be useful for aspiring Data Analysts because it provides hands-on experience with BigQuery, a powerful tool for data analysis.
For more career information including salaries, visit:
OpenCourser.com/course/rnwwa2/exploring
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
Exploring NCAA Data with BigQuery.
Is considered a classic in the field of basketball analytics, and provides a detailed explanation of how to use statistics to evaluate player and team performance. It includes a wealth of data and analysis, and valuable resource for anyone who wants to learn more about the subject.
Save
For learners who want to delve deeper into the world of basketball analytics, this book is an invaluable resource. It covers advanced concepts and techniques, and provides detailed explanations of how they can be used to evaluate player and team performance.
Save
Provides a detailed explanation of how to use statistics to evaluate player and team performance in baseball. It includes a wealth of data and analysis, and valuable resource for anyone who wants to learn more about the subject.
Save
Is considered a classic in the field of baseball analytics, and provides a comprehensive overview of the subject. It includes a wealth of data and analysis, and valuable resource for anyone who wants to learn more about the subject.
Provides a comprehensive overview of the world of soccer economics, and discusses how data can be used to evaluate player and team performance. It includes a wealth of insights and analysis, and valuable resource for anyone who wants to learn more about the subject.
Save
Tells the story of how the Oakland Athletics used analytics to build a successful baseball team on a small budget. It great choice for learners who want to learn more about the practical applications of baseball analytics.
Save
Provides an accessible introduction to the world of soccer analytics, and explains how data can be used to evaluate player and team performance. It includes a wealth of practical examples and case studies, and great choice for learners who want to learn more about the subject.
Provides the official rules of baseball, and valuable resource for anyone who wants to learn more about the sport. It includes detailed explanations of all the rules, as well as examples of how they are applied in practice.
This comprehensive and entertaining book provides a historical and cultural overview of basketball, and includes in-depth analysis of some of the greatest players and teams in the sport's history.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/rnwwa2/exploring
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Effort
45 Minutes
Level
Introductory
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
English
Good to know
Teaches how to use BigQuery to explore sports data
Uses a self-paced lab that takes place in the Google Cloud console
Instructors are Google Cloud Training, who has expertise in teaching cloud computing concepts
Provides an opportunity to explore the NCAA dataset of basketball games, teams, and players
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