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NCAA® March Madness®: Bracketology with Google Cloud

Fundamental 4 passaggi 3 ore 11 crediti

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.

Data Machine Learning

Quest Outline

Lab pratico

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.

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Lab pratico

BigQuery: Qwik Start - Command Line

Questo lab pratico illustra come eseguire query su tabelle pubbliche e caricare dati di esempio in BigQuery utilizzando l'interfaccia a riga di comando. Guarda questi brevi video: Get Meaningful Insights with Google BigQuery e BigQuery: Qwik Start - Qwiklabs Preview.

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Lab pratico

Introduction to SQL for BigQuery and Cloud SQL

In questo lab apprenderai clausole SQL di base e proverai in prima persona a eseguire query strutturate su BigQuery e Cloud SQL.

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Lab pratico

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 pratico

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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