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NCAA® March Madness®: Bracketology with Google Cloud

date_range 3 hours show_chart Fundamental universal_currency_alt 11 Credits

In this series of labs you will learn how to use BigQuery to analyze NCAA basketball data with SQL. Build a Machine Learning Model to predict the outcomes of NCAA March Madness basketball tournament games.

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  • Lab

    Using BigQuery in the Google Cloud Console

    This lab shows you how to query public tables and load sample data into BigQuery using the GCP Console. Watch the following short video Get Meaningful Insights with Google BigQuery.

    Lab

    BigQuery: Qwik Start - Command Line

    This hands-on lab shows you how to query public tables and load sample data into BigQuery using the Command Line Interface. Watch the short videos Get Meaningful Insights with Google BigQuery and BigQuery: Qwik Start - Qwiklabs Preview.

  • Lab

    Introduction to SQL for BigQuery and Cloud SQL

    In this lab you will learn fundamental SQL clauses and will get hands on practice running structured queries on BigQuery and Cloud SQL.

  • Lab

    Exploring NCAA Data with BigQuery

    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.

  • Lab

    Bracketology with Google Machine Learning

    In this lab you use Machine Learning (ML) to analyze the public NCAA dataset and predict NCAA tournament brackets.

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