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    <fireside:genDate>Tue, 27 Oct 2026 06:46:59 +0000</fireside:genDate>
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    <title>Artists of Intelligence with Harpreet Sahota - Episodes Tagged with “G”</title>
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    <pubDate>Mon, 11 May 2020 00:00:00 -0400</pubDate>
    <description>I’m relaunching the show with a different focus. It’s called Artists of Intelligence. It’s about the people building physical AI, robotics, perception, and autonomous systems. I’m not here pretending to be an expert who has it all figured out. I’m here because I want to learn, hack on things, and see how intelligent machines actually work in the real world. Before I record with anyone, I like to get hands-on with what they’re building—an open repo, a dataset, an SDK, or a demo. I play around with it and break things beforehand so we can skip the introductory fluff and have an honest conversation about how it works, what broke along the way, and what it actually takes to build. Formerly The Artists of Data Science.</description>
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    <itunes:subtitle>~/artists_of_intelligence</itunes:subtitle>
    <itunes:author>Harpreet Sahota</itunes:author>
    <itunes:summary>I’m relaunching the show with a different focus. It’s called Artists of Intelligence. It’s about the people building physical AI, robotics, perception, and autonomous systems. I’m not here pretending to be an expert who has it all figured out. I’m here because I want to learn, hack on things, and see how intelligent machines actually work in the real world. Before I record with anyone, I like to get hands-on with what they’re building—an open repo, a dataset, an SDK, or a demo. I play around with it and break things beforehand so we can skip the introductory fluff and have an honest conversation about how it works, what broke along the way, and what it actually takes to build. Formerly The Artists of Data Science.</itunes:summary>
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    <itunes:keywords>physical ai, robotics, autonomous systems, spatial ai, computer vision, embodied ai, sensor fusion, agents</itunes:keywords>
    <itunes:owner>
      <itunes:name>Harpreet Sahota</itunes:name>
      <itunes:email>hello@employabledatascientist.com</itunes:email>
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  <title>Embrace Diversity in Data Science  |  Brandeis Marshall, Phd</title>
  <link>https://harpreet.fireside.fm/brandeis-marshall</link>
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  <pubDate>Mon, 11 May 2020 00:00:00 -0400</pubDate>
  <author>Harpreet Sahota</author>
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  <itunes:episodeType>full</itunes:episodeType>
  <itunes:season>2</itunes:season>
  <itunes:author>Harpreet Sahota</itunes:author>
  <itunes:subtitle>Dr. Marshall stops by the show to discuss how she broke into data science, her research involving social media, the #BlackTwitterProject, plus the why's and how's of embracing diversity and equity in the tech world.

Join the FREE open Slack mastermind community where I'll answer questions and keep you posted on bi-weekly office hours: https://bit.ly/artistsofdatascience</itunes:subtitle>
  <itunes:duration>49:50</itunes:duration>
  <itunes:explicit>yes</itunes:explicit>
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  <description>&lt;p&gt;On this episode of The Artists of Data Science, we get a chance to hear from Brandeis Marshall, a computer scientist that is excellent at breaking down difficult concepts into easily digestible pieces. &lt;/p&gt;

&lt;p&gt;She is passionate about educating people on data, as well as understanding the impact data has on race, gender, and socio-economic disparities. &lt;/p&gt;

&lt;p&gt;She is the CEO of DataEdx, a company which focuses on making data science accessible to all professionals.&lt;/p&gt;

&lt;p&gt;She shares her perspective on how data impacts communities, how to promote diversity and inclusion in the data science space, and the importance of documenting your process. It was an absolute pleasure to hear her perspective, and I believe her message will help broaden the data science field.&lt;/p&gt;

&lt;p&gt;WHAT YOU WILL LEARN&lt;/p&gt;

&lt;p&gt;[8:29] How data impacts marginalized communities&lt;/p&gt;

&lt;p&gt;[13:29] From Brandeis's perspective, what separates great data scientist from good ones&lt;/p&gt;

&lt;p&gt;[14:48] Understanding how data is packaged, and ways to break it down into bite-size portions&lt;/p&gt;

&lt;p&gt;[19:30] The impact of live tweeting on social movements&lt;/p&gt;

&lt;p&gt;[30:09] Discussing inclusiveness in the data workspace&lt;/p&gt;

&lt;p&gt;[39:46] How to be gritty and break away from negative thoughts&lt;/p&gt;

&lt;p&gt;QUOTES&lt;br&gt;
[7:57] "I'm trying to do my best to be… that beacon to talk about data in sizeable, understandable nuggets, because it's not just a science thing. It is our everyday life."&lt;/p&gt;

&lt;p&gt;[11:45] "…if you stay within your own lane in your own expertise, only talking to people who have your particular background, you're losing the whole story… and with data, there's always a story"&lt;/p&gt;

&lt;p&gt;[29:34] "…I want…other people to know that they can talk about their particular ethnicities, content in a research space, in the tech space, and still be successful."&lt;/p&gt;

&lt;p&gt;FIND BRANDEIS ONLINE&lt;/p&gt;

&lt;p&gt;Twitter: &lt;a href="https://twitter.com/csdoctorsister" rel="nofollow noopener"&gt;https://twitter.com/csdoctorsister&lt;/a&gt;&lt;/p&gt;

&lt;p&gt;LinkedIn: &lt;a href="https://www.linkedin.com/in/brandeis-marshall/" rel="nofollow noopener"&gt;https://www.linkedin.com/in/brandeis-marshall/&lt;/a&gt;&lt;/p&gt;

&lt;p&gt;Website: &lt;a href="https://www.brandeismarshall.com/" rel="nofollow noopener"&gt;https://www.brandeismarshall.com/&lt;/a&gt;&lt;/p&gt;

&lt;p&gt;DataedX: &lt;a href="https://www.dataedx.com/" rel="nofollow noopener"&gt;https://www.dataedx.com/&lt;/a&gt;&lt;/p&gt;

&lt;p&gt;SHOW NOTES&lt;br&gt;
[00:01:50] Introduction for our guest today&lt;/p&gt;

&lt;p&gt;[00:04:51] Brandeis talks to us about how she heard of data science. What drew her to the field and some of the struggles and challenges she faced as she were breaking into the field&lt;/p&gt;

&lt;p&gt;[00:07:21] Break data in sizeable, understandable nuggets.&lt;/p&gt;

&lt;p&gt;[00:08:21] So where do you see the field headed in the next two to five years?&lt;/p&gt;

&lt;p&gt;[00:09:12] How do we shift the conversation so that all people are included in the data conversation?&lt;/p&gt;

&lt;p&gt;[00:10:39] What could data scientists start doing today so that two to five years in the future they understand the need for diversity of data and they're cognizant of it. What are some things that they could start doing today?&lt;/p&gt;

&lt;p&gt;[00:11:03] Data scientists need to get out of their comfort zone&lt;/p&gt;

&lt;p&gt;[00:13:12] How to be a great data scientist&lt;/p&gt;

&lt;p&gt;[00:14:27] What is data competency&lt;/p&gt;

&lt;p&gt;[00:16:38] What's the mission for your new startup, DataEdX?&lt;/p&gt;

&lt;p&gt;[00:19:30] Live tweeting, social movements, and data science&lt;/p&gt;

&lt;p&gt;[00:22:28] The technical aspects of the Black twitter project&lt;/p&gt;

&lt;p&gt;[00:27:31] Project Ideas for Data Scientists&lt;/p&gt;

&lt;p&gt;[00:29:04] If there is any impact that you want your work in this space to have on society as a whole?&lt;/p&gt;

&lt;p&gt;[00:30:08] The unfortunate effects marginalization in the data workspace&lt;/p&gt;

&lt;p&gt;[00:33:30] Diversity in data science&lt;/p&gt;

&lt;p&gt;[00:36:34] Dispelling the myth of "it's all about technical skills" and questioning the "move fast" ideology in tech.&lt;/p&gt;

&lt;p&gt;[00:39:46] Grit and being determined to seeing your goals through even in the face of challenges.&lt;/p&gt;

&lt;p&gt;[00:43:05] What's the one thing you want people to learn from your story.&lt;/p&gt;

&lt;p&gt;[00:43:23] The lightning round&lt;/p&gt;&lt;p&gt;Special Guest: Brandeis Marshall, PhD.&lt;/p&gt;</description>
  <itunes:keywords>Data Science, Machine Learning, Math, Statistics, Journey, AI, Growth Mindset, Passion, Persistence, Grit, equity, diversity, black twitter</itunes:keywords>
  <content:encoded>
    <![CDATA[<p>On this episode of The Artists of Data Science, we get a chance to hear from Brandeis Marshall, a computer scientist that is excellent at breaking down difficult concepts into easily digestible pieces. </p>

<p>She is passionate about educating people on data, as well as understanding the impact data has on race, gender, and socio-economic disparities. </p>

<p>She is the CEO of DataEdx, a company which focuses on making data science accessible to all professionals.</p>

<p>She shares her perspective on how data impacts communities, how to promote diversity and inclusion in the data science space, and the importance of documenting your process. It was an absolute pleasure to hear her perspective, and I believe her message will help broaden the data science field.</p>

<p>WHAT YOU WILL LEARN</p>

<p>[8:29] How data impacts marginalized communities</p>

<p>[13:29] From Brandeis's perspective, what separates great data scientist from good ones</p>

<p>[14:48] Understanding how data is packaged, and ways to break it down into bite-size portions</p>

<p>[19:30] The impact of live tweeting on social movements</p>

<p>[30:09] Discussing inclusiveness in the data workspace</p>

<p>[39:46] How to be gritty and break away from negative thoughts</p>

<p>QUOTES<br>
[7:57] "I'm trying to do my best to be… that beacon to talk about data in sizeable, understandable nuggets, because it's not just a science thing. It is our everyday life."</p>

<p>[11:45] "…if you stay within your own lane in your own expertise, only talking to people who have your particular background, you're losing the whole story… and with data, there's always a story"</p>

<p>[29:34] "…I want…other people to know that they can talk about their particular ethnicities, content in a research space, in the tech space, and still be successful."</p>

<p>FIND BRANDEIS ONLINE</p>

<p>Twitter: <a href="https://twitter.com/csdoctorsister" rel="nofollow noopener">https://twitter.com/csdoctorsister</a></p>

<p>LinkedIn: <a href="https://www.linkedin.com/in/brandeis-marshall/" rel="nofollow noopener">https://www.linkedin.com/in/brandeis-marshall/</a></p>

<p>Website: <a href="https://www.brandeismarshall.com/" rel="nofollow noopener">https://www.brandeismarshall.com/</a></p>

<p>DataedX: <a href="https://www.dataedx.com/" rel="nofollow noopener">https://www.dataedx.com/</a></p>

<p>SHOW NOTES<br>
[00:01:50] Introduction for our guest today</p>

<p>[00:04:51] Brandeis talks to us about how she heard of data science. What drew her to the field and some of the struggles and challenges she faced as she were breaking into the field</p>

<p>[00:07:21] Break data in sizeable, understandable nuggets.</p>

<p>[00:08:21] So where do you see the field headed in the next two to five years?</p>

<p>[00:09:12] How do we shift the conversation so that all people are included in the data conversation?</p>

<p>[00:10:39] What could data scientists start doing today so that two to five years in the future they understand the need for diversity of data and they're cognizant of it. What are some things that they could start doing today?</p>

<p>[00:11:03] Data scientists need to get out of their comfort zone</p>

<p>[00:13:12] How to be a great data scientist</p>

<p>[00:14:27] What is data competency</p>

<p>[00:16:38] What's the mission for your new startup, DataEdX?</p>

<p>[00:19:30] Live tweeting, social movements, and data science</p>

<p>[00:22:28] The technical aspects of the Black twitter project</p>

<p>[00:27:31] Project Ideas for Data Scientists</p>

<p>[00:29:04] If there is any impact that you want your work in this space to have on society as a whole?</p>

<p>[00:30:08] The unfortunate effects marginalization in the data workspace</p>

<p>[00:33:30] Diversity in data science</p>

<p>[00:36:34] Dispelling the myth of "it's all about technical skills" and questioning the "move fast" ideology in tech.</p>

<p>[00:39:46] Grit and being determined to seeing your goals through even in the face of challenges.</p>

<p>[00:43:05] What's the one thing you want people to learn from your story.</p>

<p>[00:43:23] The lightning round</p><p>Special Guest: Brandeis Marshall, PhD.</p>]]>
  </content:encoded>
  <itunes:summary>
    <![CDATA[<p>On this episode of The Artists of Data Science, we get a chance to hear from Brandeis Marshall, a computer scientist that is excellent at breaking down difficult concepts into easily digestible pieces. </p>

<p>She is passionate about educating people on data, as well as understanding the impact data has on race, gender, and socio-economic disparities. </p>

<p>She is the CEO of DataEdx, a company which focuses on making data science accessible to all professionals.</p>

<p>She shares her perspective on how data impacts communities, how to promote diversity and inclusion in the data science space, and the importance of documenting your process. It was an absolute pleasure to hear her perspective, and I believe her message will help broaden the data science field.</p>

<p>WHAT YOU WILL LEARN</p>

<p>[8:29] How data impacts marginalized communities</p>

<p>[13:29] From Brandeis's perspective, what separates great data scientist from good ones</p>

<p>[14:48] Understanding how data is packaged, and ways to break it down into bite-size portions</p>

<p>[19:30] The impact of live tweeting on social movements</p>

<p>[30:09] Discussing inclusiveness in the data workspace</p>

<p>[39:46] How to be gritty and break away from negative thoughts</p>

<p>QUOTES<br>
[7:57] "I'm trying to do my best to be… that beacon to talk about data in sizeable, understandable nuggets, because it's not just a science thing. It is our everyday life."</p>

<p>[11:45] "…if you stay within your own lane in your own expertise, only talking to people who have your particular background, you're losing the whole story… and with data, there's always a story"</p>

<p>[29:34] "…I want…other people to know that they can talk about their particular ethnicities, content in a research space, in the tech space, and still be successful."</p>

<p>FIND BRANDEIS ONLINE</p>

<p>Twitter: <a href="https://twitter.com/csdoctorsister" rel="nofollow noopener">https://twitter.com/csdoctorsister</a></p>

<p>LinkedIn: <a href="https://www.linkedin.com/in/brandeis-marshall/" rel="nofollow noopener">https://www.linkedin.com/in/brandeis-marshall/</a></p>

<p>Website: <a href="https://www.brandeismarshall.com/" rel="nofollow noopener">https://www.brandeismarshall.com/</a></p>

<p>DataedX: <a href="https://www.dataedx.com/" rel="nofollow noopener">https://www.dataedx.com/</a></p>

<p>SHOW NOTES<br>
[00:01:50] Introduction for our guest today</p>

<p>[00:04:51] Brandeis talks to us about how she heard of data science. What drew her to the field and some of the struggles and challenges she faced as she were breaking into the field</p>

<p>[00:07:21] Break data in sizeable, understandable nuggets.</p>

<p>[00:08:21] So where do you see the field headed in the next two to five years?</p>

<p>[00:09:12] How do we shift the conversation so that all people are included in the data conversation?</p>

<p>[00:10:39] What could data scientists start doing today so that two to five years in the future they understand the need for diversity of data and they're cognizant of it. What are some things that they could start doing today?</p>

<p>[00:11:03] Data scientists need to get out of their comfort zone</p>

<p>[00:13:12] How to be a great data scientist</p>

<p>[00:14:27] What is data competency</p>

<p>[00:16:38] What's the mission for your new startup, DataEdX?</p>

<p>[00:19:30] Live tweeting, social movements, and data science</p>

<p>[00:22:28] The technical aspects of the Black twitter project</p>

<p>[00:27:31] Project Ideas for Data Scientists</p>

<p>[00:29:04] If there is any impact that you want your work in this space to have on society as a whole?</p>

<p>[00:30:08] The unfortunate effects marginalization in the data workspace</p>

<p>[00:33:30] Diversity in data science</p>

<p>[00:36:34] Dispelling the myth of "it's all about technical skills" and questioning the "move fast" ideology in tech.</p>

<p>[00:39:46] Grit and being determined to seeing your goals through even in the face of challenges.</p>

<p>[00:43:05] What's the one thing you want people to learn from your story.</p>

<p>[00:43:23] The lightning round</p><p>Special Guest: Brandeis Marshall, PhD.</p>]]>
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