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NCAA® March Madness®: Bracketology with Google Cloud

Fundamental 4 Steps 2h 45m 11 积分

NCAA GCP

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

Data Machine Learning

Quest Outline

Hands-On Lab

Using the BigQuery Web UI

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

Hands-On 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.

Deutsch English español (Latinoamérica) français 日本語 português (Brasil)
Hands-On 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.

Deutsch English español (Latinoamérica) français 日本語 português (Brasil)
Hands-On 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.

Hands-On 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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