arrow_back

NCAA® March Madness®: Bracketology with Google Cloud

share

NCAA® March Madness®: Bracketology with Google Cloud

3 hours 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.

Complete this activity and earn a badge! Boost your cloud career by showing the world the skills you’ve developed.

  • 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 - Komut Satırı

    Bu uygulamalı laboratuvarda, herkese açık tabloları nasıl sorgulayacağınız ve örnek verileri Komut Satırı Arayüzünü kullanarak nasıl BigQuery'ye yükleyeceğiniz gösterilmektedir. Google BigQuery ile Anlamlı Analizler Elde Etme ve BigQuery: Qwik Start - Qwiklabs Önizlemesi başlıklı kısa videoları izleyin.

  • Lab

    BigQuery ve Cloud SQL için SQL'e giriş

    Bu laboratuvarda SQL ile ilgili temel koşulları öğrenecek, BigQuery ve Cloud SQL'de yapılandırılmış sorgular çalıştırma hakkında uygulamalı alıştırmalar yapacaksınız.

  • 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.

  • info
    Quest Info