Here's How Jacky Sawyer Improved Data Utilization with Our Data Science Bootcamp
After completing our 5-day bootcamp, Jacky returned to Breaking Ground* with the goal of improving how the non-profit organization utilizes the information that they collect.
Jacky was able to create a highly detailed inventory of all the data that Breaking Ground has, and used that information to begin the development of a more robust data analytics strategy. Breaking Ground was also able to start building an ETL process to feed into a data warehouse.
Jacky believes that by attending Data Science Dojo, she was able to return to her work with new questions and ideas for how to improve their data utilization and use that information for good.
*Breaking Ground is a large nonprofit in New York City that provides housing opportunities for low-income and formerly homeless individuals as well as a street outreach program for the most vulnerable citizens.
Watch more Case Studies:
https://datasciencedojo.com/bootcamp/case-studies/
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https://hubs.ly/H0hDdnN0
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https://hubs.ly/H0hDdD10
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At Data Science Dojo, we believe data science is for everyone. Our in-person data science training has been attended by more than 4000+ employees from over 830 companies globally, including many leaders in tech like Microsoft, Apple, and Facebook.
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#datascience #dataengineering #datanalytics #datasciencebootcamp
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Feature Engineering and Predictive Modeling | Data Analytics with R and Azure ML | Community Webinar
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Data Exploration and Visualization | Beginning Azure ML | Part 3
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Reading External Data Sources | Beginning Azure ML | Part 2
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Importing Data, Accessing, & Creating a New Experiment | Beginning Azure ML | Part 1
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Casting Columns & Renaming Columns | Beginning Azure ML | Part 4
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Scrub Missing Values & Project Columns | Beginning Azure ML | Part 5
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Feature Engineering & R Script | Beginning Azure ML | Part 6
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Building Your First Model | Beginning Azure ML | Part 7
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Run and Fine-Tune Multiple Models | Beginning Azure ML | Part 8
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Deploying Your First Predictive Model As a Web Service | Beginning Azure ML | Part 9
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Using R API to Obtain Predictions From Your Web Service Beginning Azure ML | Part 10
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Using Python API to Obtain Predictions From Your Web Service | Beginning Azure ML | Part 11
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Twitter Sentiment Analysis | Natural Language Processing | Community Webinar
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Listening to the Melody of the Universe (LIGO Gravitational Waves Presentation) | Community Webinar
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Software Engineer at Microsoft Reveals About His Experience with Data Science Bootcamp
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Wade Wimer on the Impact of Data Science Bootcamp
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Analyzing Data with Data Science Bootcamp: Hannah Richta's Revelation
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Text Analytics With Python, Cognitive Services & PowerBI | Data Analytics | Community Webinar
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Learn Data Mining with Data Science Bootcamp: Ryan LaBrie's Revelation
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Vang Xiong on the Impact of Data Science Bootcamp
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Data Scientist's Experience at Our Data Science Bootcamp
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Alejandro Wolf Yadlin on the Impact of Data Science Bootcamp
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Introduction To Titanic Kaggle Competition | Part 1
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Learning How to Code in R with Data Science Bootcamp: Priscilla Mannuel's Revelation
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Andrew Berman On Why Data Science Bootcamp Is Better Fit for Him
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How To Do Titanic Kaggle Competition in R | Part 3.1
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How to do the Titanic Kaggle competition in R | Part 3.1
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Types of Sampling | Introduction to Data Mining | Part 12
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Sampling for Data Selection | Introduction to Data Mining | Part 11
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Data Aggregation | Introduction to Data Mining | Part 10
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Data Cleaning | Introduction to Data Mining | Part 9
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Missing & Duplicated Data | Introduction to Data Mining | Part 8
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Data Noise | Introduction to Data Mining | Part 7
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