<p>We&#39;re releasing episode 17 of our DataChats video series. In this episode, Hugo is interviewing Daniel Chen!</p>

<p>Daniel is a Software Carpentry instructor and a doctoral student in Genetics, Bioinformatics, and Computational Biology at Virginia Tech, where he works in the Social and Decision Analytics Laboratory under the Biocomplexity Institute. He received his MPH at the Mailman School of Public Health in Epidemiology and is interested in integrating hospital data in order to perform predictive health analytics and build clinical support tools for clinicians. An advocate of open science, he aspires to bridge data science with epidemiology and health care. You can take his course here <a href="https://www.datacamp.com/courses/cleaning-data-in-python">Cleaning Data in Python</a>.&nbsp;</p>

<p>In this episode, Daniel talks about his upcoming book, whether to start learning python or R for data science, the best paths to becoming a data scientist, and much more.</p>

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<center><iframe allowfullscreen="" frameborder="0" height="315" src="https://www.youtube.com/embed/2rhmd64gg3o" width="560"></iframe></center>

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<p>We hope that you enjoy watching this series and make sure not to miss any of our upcoming episodes by subscribing to&nbsp;<strong><a href="https://www.youtube.com/channel/UC79Gv3mYp6zKiSwYemEik9A">DataCamp&#39;s YouTube channel!</a></strong></p>


https://www.datacamp.com/community/blog/datachats-an-interview-with-daniel-chen

An interview with Daniel Chen, creator of the "Cleaning Data with Python" course, about learning Python or R for data science, the best paths to becoming a data scientist,...

An interview with Daniel Chen, creator of DataCamp's Cleaning Data with Python course, about learning Python or R for data science and much more!

DataChats: An Interview with Daniel Chen

<p>We&#39;re releasing episode 16 of our DataChats video series. And today, Hugo is interviewing Peter Bull, co-founder of DrivenData.</p>

<p>Peter&nbsp;earned his master&#39;s in Computational Science and Engineering from Harvard&rsquo;s School of Engineering and Applied Sciences. His work lies at the intersection of statistics and computer science, and he wants to help bring powerful new modeling techniques to the organizations that need them most. He previously worked as a software engineer at Microsoft and earned a BA in philosophy from Yale University. You can take his&nbsp;DataCamp course here <a href="https://www.datacamp.com/courses/machine-learning-with-the-experts-school-budgets/">Machine Learning with the Experts: School Budgets.</a></p>

<p>In this episode, Peter and Hugo discuss why use python for data science, the challenge of finding the business case for data, DrivenData competitions on using yelp data to predict restaurant sanitary ratings and much more.</p>

<center><iframe allowfullscreen="" frameborder="0" height="315" src="https://www.youtube.com/embed/8jMZkaqMiZc" width="560"></iframe></center>

<section>
<p>We hope that you enjoy watching this series and make sure not to miss any of our upcoming episodes by subscribing to&nbsp;<strong><a href="https://www.youtube.com/channel/UC79Gv3mYp6zKiSwYemEik9A">DataCamp&#39;s YouTube channel!</a></strong></p>
</section>


https://www.datacamp.com/community/blog/datachats-an-interview-with-peter-bull

Peter Bull, author of DataCamp course "Machine Learning with the Experts: School Budgets", answers Hugo's questions in episode 16 of DataChats!

Peter Bull, author of DataCamp course Machine Learning with the Experts: School Budgets, answers Hugo's questions in episode 16 of DataChats!

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