Live training with Joy Payton starts on March 10th at 12 PM (EST)

Training duration: 4 hours (Hands-on)

Price with 30% discount

Regular Price: $210.00

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Instructor Bio:

Supervisor of Data Education | Children's Hospital of Philadelphia

Joy Payton

Joy Payton is a data scientist and data educator at the Children’s Hospital of Philadelphia (CHOP), where she helps biomedical researchers learn the reproducible computational methods that will speed time to science and improve the quality and quantity of research conducted at CHOP. A longtime open source evangelist, Joy develops and delivers data science instruction on topics related to R, Python, and git to an audience that includes physicians, nurses, researchers, analysts, developers, and other staff. Her personal research interests include using natural language processing to identify linguistic differences in a neurodiverse population as well as the use of government open data portals to conduct citizen science that draws attention to issues affecting vulnerable groups. Joy holds a degree in philosophy and math from Agnes Scott College, a divinity degree from the Universidad Pontificia de Comillas (Madrid), and a data science Master's from the City University of New York (CUNY).

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Learning Objectives

  • Be able to make the case for cloud hosted data at work (or understand why it's not a good fit for your business)

  • Make discoveries in data using BigQuery

  • Create analytics notebooks you can share with stakeholders

DIFFICULTY LEVEL: INTERMEDIATE

Course Outline

Module 1: Intro to Presenter and GCP 

  • Presenter intro
  • What is Google Cloud Platform?
  • Signing up with an existing or new Google identity
  • Pricing and staying in the "free tier"
  • Hands-on: Sign up for Google Identity and Google Cloud Platform
  • Break



Module 2: The Basics of BigQuery 

  • Presentation: Big data means big solutions!  A comparison of Google's data solutions with an emphasis on BigQuery and its public datasets 
  • Guided / Interactive Exercise: Create a new project and open BigQuery, preview a number of public datasets
  • Presentation: SQL Refresher and SQL in BigQuery -- SELECT, FROM, WHERE, aliases, whitespace,  BigQuery billing / SQL validator  
  • Hands On Exercise: Running (given) queries against BigQuery public datasets (includes Views and table creation), fixing broken queries with simple errors
  • Break



Module 3: Using your own data 

  • Intro to Google Cloud Storage (GCS)
  • Presentation: Importing data into BigQuery 
  • Hands on Exercise: Create a dataset and import a table


Module 4: Intermediate SQL Querying in BigQuery 

  • Presentation: Aggregation using GROUP BY + COUNT, statistical and other functions
  • Exercise: Practicing with aggregation 
  • Presentation: JOINs and common pitfalls (Cartesian JOINS, etc.) 
  • Exercise: Practicing with JOINs (with With clauses) 
  • Presentation: Custom functions and working with strings 
  • Hands On Exercise: String functions 
  • Break


Module 5: Going Deeper -- From Knowledge to Insight

  • Presentation: Advanced Querying in BigQuery
  • Presentation: Introduction to Colab notebooks 
  • Hands on Exercise: Create a new Colab notebook, save it, add sharing settings
  • Presentation: three ways to integrate BigQuery SQL queries into Colab notebooks
  • Hands On Exercise: Come up with the right query for the job and add it to a notebook 

Abstract

In this session, we'll get you started with the Google Cloud Platform. By concentrating on relational data, we'll not only learn a lot about cloud computing, but we'll also delve into SQL, which is ubiquitous in data systems in every company and non-profit.

Specifically, we'll look at Google Cloud Platform’s very large SQL solution, called BigQuery. We'll reinforce basic SQL, help you grow your BigQuery SQL skills, and leave you with all the tools you need to continue practicing after the course ends.  All our work will take place in GCP's free service tier -- so you can take what you've worked on, leverage it, and make brand-new discoveries long after our course ends.

If you haven't known how to get started with the cloud, and you're looking to exercise rusty SQL skills or want to get started with SQL, this session will be great for you.

What background knowledge you should have?

  • Some experience with data manipulation -- calculating monthly sales in Excel, comparing two groups in SPSS, etc.

  • A grasp of relational data and basic SQL queries

  • A gmail address or other Google identity

  • A computer with the Chrome web browser on a network that permits access to Google products (be aware that your company may block this on their network)

  • A Google Cloud Platform account (free to sign up)

  • Helpful, but not required: a basic grasp of Python

What is included in your ticket?

  • Access to live training and QA session with the Instructor

  • Access to the on-demand recording

  • Certificate of completion

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