LIVE TRAINING

SAVE THE DATE: March 10th, 2022 @ 12 pm EST

REGISTER HERE NOW

Joy Payton is a cloud engineer, data scientist, and adjunct professor who specializes in helping biomedical professionals conduct reproducible computational research.

LIVE TRAINING: Introduction to PYTHON for Programming 

October 12th @12 PM EST

Save 30% : Register Now

Price: $147

Regular price $210, discounted 10%
  • 4 hour immersive session

  • Hands-on training with Q&A

  • Recording available on-demand

  • Certification of Completion

30% Discount Ends in:

Subscribe and get an additional 10% to 35% off ALL live training session
View Plans

Pricing: $147

Regular price $210, discounted 30%
  • 4 hour immersive session

  • Hands-on training with Q&A

  • Recording available on-demand

  • Certification of Completion

30% Discount Ends in:

Subscribe and get an additional 10% to 35% off ALL live training session
View Plans

Meet Your Instructor

Joy Payton

Joy Payton is a cloud engineer, data scientist, and adjunct professor who specializes in helping biomedical professionals conduct reproducible computational research. In addition to moving medicine forward through principles of open science and reproducibility, Joy also enjoys teaching citizen scientists how to use public data repositories to understand their own communities better and advocate for change from a data-centric perspective. Her various roles allow Joy to lead efforts to teach people how to write their first line of code and help anyone who’s interested climb the data science learning curve. Currently employed by the Children’s Hospital of Philadelphia and Yeshiva University, Joy is always open to hearing about open-source, data-centric volunteer opportunities for herself and her students.

Course Overview

What’s the plan? 

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.

Course Outline

What’s the plan? 

Matt Harrison has been working with Python and data since 2000. He has a computer science degree from Stanford. He has worked at many amazing companies, created cool products, wrote a couple books, and taught thousands Python and Data Science. Currently, he is working as a corporate trainer, author, and consultant through his company Metasnake, which provides consulting and teaches corporations how to be effective with Python and data science.

Course Overview

Python is a powerful tools that XXX

Join the live session with Joy Payton

SAVE 30%

Course Outline

Module 1:
Intro to Presenter and GCP

Module 2:
The Basics of BigQuery  

Module 3:
Using your own data

Module 4:
Intermediate SQL Querying in BigQuery

Module 5:
Going Deeper – From Knowledge to Insight

  • 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
  • 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
  • Intro to Google Cloud Storage (GCS)
  • Presentation: Importing data into BigQuery
  • Hands-on Exercise: Create a dataset and import a table
  • 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
  • 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
  • Q&A and close (5m)

Key on emojidex Key Details

DATE

TIME:

DURATION:

LEVEL:

March 10Th, 2022

TIME: 12 PM EST

4 HOURS

INTERMEDIATE

Prerequisites

  • 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

Upcoming Live Training

March 16th, 2022

Part 4. Natural Language Processing
 
This course is divided in 3 main topics: deep learning for NLP, modelling natural language data and recurrent and advanced neural networks. In the first topic, we will focus on easy, intermediate, and complex NLP applications, word vectors: representing language as embeddings and an interactive visualization of vector-space embeddings. In the second topic, the course will cover using word2vec to create word vectors and document classification with a dense neural network and convolutional neural network. In the final topic, you will learn about RNNs, LSTMs and transformers: BERT, ELMo & Friends.
learn more

Upcoming Live Training

XXth

XXX

XXX.

learn more
Open Data Science

Ai+ | ODSC
One Broadway, 14th Floor
Cambridge, MA 02142
admin_aiplus@odsc.com

Privacy Settings
We use cookies to enhance your experience while using our website. If you are using our Services via a browser you can restrict, block or remove cookies through your web browser settings. We also use content and scripts from third parties that may use tracking technologies. You can selectively provide your consent below to allow such third party embeds. For complete information about the cookies we use, data we collect and how we process them, please check our Privacy Policy
Youtube
Consent to display content from - Youtube
Vimeo
Consent to display content from - Vimeo
Google Maps
Consent to display content from - Google