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    <fireside:genDate>Wed, 04 Nov 2026 07:28:07 +0000</fireside:genDate>
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    <title>Artists of Intelligence with Harpreet Sahota - Episodes Tagged with “Data Scientist”</title>
    <link>https://harpreet.fireside.fm/tags/data%20scientist</link>
    <pubDate>Fri, 27 Aug 2021 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:explicit>no</itunes:explicit>
    <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>The Ambition | Jeff Li</title>
  <link>https://harpreet.fireside.fm/jeff-li</link>
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  <pubDate>Fri, 27 Aug 2021 00:00:00 -0400</pubDate>
  <author>Harpreet Sahota</author>
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  <itunes:episodeType>full</itunes:episodeType>
  <itunes:season>15</itunes:season>
  <itunes:author>Harpreet Sahota</itunes:author>
  <itunes:subtitle></itunes:subtitle>
  <itunes:duration>1:10:04</itunes:duration>
  <itunes:explicit>yes</itunes:explicit>
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  <description>&lt;p&gt;MEMORABLE QUOTES &lt;br&gt;
[00:11:51] “..and then once you kind of clearly define exactly the outcome that you’re aiming for, it makes it a little bit easier to start breaking it down into chunks.”&lt;/p&gt;

&lt;p&gt;[00:28:51] “ There are so many things that are outside of control. Just don’t even worry about those but focus on the things you can control.”&lt;/p&gt;

&lt;p&gt;[00:38:28] “…having too much of it can be crippling but having a little bit can actually motivate you and push you to continue to grow your skillset which, ultimately, is beneficial to you and everybody around you.”&lt;/p&gt;

&lt;p&gt;[00:40:15] “Fear is a powerful emotion. If you can wrestle it and have it push you from behind rather than block you, you learn whatever it is you’ve got to learn and improve and grow.“&lt;/p&gt;

&lt;p&gt;[00:54:45] “As you provide more value and you’re reliable and you are providing good work, your influence will gradually grow.”&lt;/p&gt;

&lt;p&gt;[01:02:12] “ I guess I’d want to be remembered for somebody who took on very difficult ambitious challenges where I knew that I had little possibility of succeeding but I still did it anyway.”&lt;/p&gt;

&lt;p&gt;HIGHLIGHTS FROM THE SHOW&lt;/p&gt;

&lt;p&gt;[00:00:51] Guest introduction.&lt;/p&gt;

&lt;p&gt;[00:02:54] Can you tell us a little bit about where you grew up and what it was like there?&lt;/p&gt;

&lt;p&gt;[00:03:42] When you were in high school, what did you think your future would look like?&lt;/p&gt;

&lt;p&gt;[00:04:43] What was the journey like from there to now?&lt;/p&gt;

&lt;p&gt;[00:06:39] What were some of the resources you used to help you figure out how to become a better learner?&lt;/p&gt;

&lt;p&gt;[00:08:37] Can you define what deliberate practice means?&lt;/p&gt;

&lt;p&gt;[00:10:18] How do we apply the concept?&lt;/p&gt;

&lt;p&gt;[00:15:23] How would you define a mental model?   &lt;/p&gt;

&lt;p&gt;[00:18:44] Which mental model would you say has had the biggest impact on the way you see the world?&lt;/p&gt;

&lt;p&gt;[00:21:27] What does the problem-centric approach mean?&lt;/p&gt;

&lt;p&gt;[00:25:47] Jeff talks about his secrets to getting multiple job offers.&lt;/p&gt;

&lt;p&gt;[00:28:51] Did you ever feel emotionally invested in one given prospect?&lt;/p&gt;

&lt;p&gt;[00:31:19] What would you say to someone scared of applying to job descriptions that look like they want the abilities of an entire team?&lt;/p&gt;

&lt;p&gt;[00:33:51] What was common among all these interviews that you went for?&lt;/p&gt;

&lt;p&gt;[00:36:21] What other nuanced things do you think a data scientist should really understand from school?&lt;/p&gt;

&lt;p&gt;[00:37:52] What is your relationship with imposter syndrome like?&lt;/p&gt;

&lt;p&gt;[00:40:15] Any words of encouragement for people trying to come back from an imposter syndrome?&lt;/p&gt;

&lt;p&gt;[00:41:49] Talk to us about the importance of having a portfolio project.&lt;/p&gt;

&lt;p&gt;[00:44:19] What are some of the biggest journalistic mistakes you’ve seen?&lt;/p&gt;

&lt;p&gt;[00:45:21] Can you tell me how you would answer the “Tell me about yourself” question in an interview?&lt;/p&gt;

&lt;p&gt;[00:47:20] If somebody wanted to a project using data from Spotify, what do you think would be a good project idea?&lt;/p&gt;

&lt;p&gt;[00:49:20] How do you use deep learning to help you find dates here?&lt;/p&gt;

&lt;p&gt;[00:51:21] What are some non-obvious skills that Data Scientists are missing that you think they should go and pick up?&lt;/p&gt;

&lt;p&gt;[00:52:45] Do you keep a journal or anything like that?&lt;/p&gt;

&lt;p&gt;[00:54:15] What tips can you share with data scientists for developing their leadership &amp;amp;influence skills?&lt;/p&gt;

&lt;p&gt;[00:58:52] What are some harsh truths about being a data scientist that you want to leave our audience with?&lt;/p&gt;

&lt;p&gt;[01:00:57] It’s 100 years in the future, what do you want to be remembered for?     &lt;/p&gt;

&lt;p&gt;[01:03:13] The Random Round.&lt;/p&gt;</description>
  <itunes:keywords>spotify, jeff li, data science OR how to become data scientist, mentor, data science mentorship, sharpest minds, data science dream job, harpreet sahota, kyle mckiou, data science dream job reviews, how to find a data science mentor, finding a data science mentor, data science office hours, free data science help, data science advice, data science career guidance, data science career mentor, how to become a data scientist, data science dream job, data science coaching</itunes:keywords>
  <content:encoded>
    <![CDATA[<p>MEMORABLE QUOTES <br>
[00:11:51] “..and then once you kind of clearly define exactly the outcome that you’re aiming for, it makes it a little bit easier to start breaking it down into chunks.”</p>

<p>[00:28:51] “ There are so many things that are outside of control. Just don’t even worry about those but focus on the things you can control.”</p>

<p>[00:38:28] “…having too much of it can be crippling but having a little bit can actually motivate you and push you to continue to grow your skillset which, ultimately, is beneficial to you and everybody around you.”</p>

<p>[00:40:15] “Fear is a powerful emotion. If you can wrestle it and have it push you from behind rather than block you, you learn whatever it is you’ve got to learn and improve and grow.“</p>

<p>[00:54:45] “As you provide more value and you’re reliable and you are providing good work, your influence will gradually grow.”</p>

<p>[01:02:12] “ I guess I’d want to be remembered for somebody who took on very difficult ambitious challenges where I knew that I had little possibility of succeeding but I still did it anyway.”</p>

<p>HIGHLIGHTS FROM THE SHOW</p>

<p>[00:00:51] Guest introduction.</p>

<p>[00:02:54] Can you tell us a little bit about where you grew up and what it was like there?</p>

<p>[00:03:42] When you were in high school, what did you think your future would look like?</p>

<p>[00:04:43] What was the journey like from there to now?</p>

<p>[00:06:39] What were some of the resources you used to help you figure out how to become a better learner?</p>

<p>[00:08:37] Can you define what deliberate practice means?</p>

<p>[00:10:18] How do we apply the concept?</p>

<p>[00:15:23] How would you define a mental model?   </p>

<p>[00:18:44] Which mental model would you say has had the biggest impact on the way you see the world?</p>

<p>[00:21:27] What does the problem-centric approach mean?</p>

<p>[00:25:47] Jeff talks about his secrets to getting multiple job offers.</p>

<p>[00:28:51] Did you ever feel emotionally invested in one given prospect?</p>

<p>[00:31:19] What would you say to someone scared of applying to job descriptions that look like they want the abilities of an entire team?</p>

<p>[00:33:51] What was common among all these interviews that you went for?</p>

<p>[00:36:21] What other nuanced things do you think a data scientist should really understand from school?</p>

<p>[00:37:52] What is your relationship with imposter syndrome like?</p>

<p>[00:40:15] Any words of encouragement for people trying to come back from an imposter syndrome?</p>

<p>[00:41:49] Talk to us about the importance of having a portfolio project.</p>

<p>[00:44:19] What are some of the biggest journalistic mistakes you’ve seen?</p>

<p>[00:45:21] Can you tell me how you would answer the “Tell me about yourself” question in an interview?</p>

<p>[00:47:20] If somebody wanted to a project using data from Spotify, what do you think would be a good project idea?</p>

<p>[00:49:20] How do you use deep learning to help you find dates here?</p>

<p>[00:51:21] What are some non-obvious skills that Data Scientists are missing that you think they should go and pick up?</p>

<p>[00:52:45] Do you keep a journal or anything like that?</p>

<p>[00:54:15] What tips can you share with data scientists for developing their leadership &amp;influence skills?</p>

<p>[00:58:52] What are some harsh truths about being a data scientist that you want to leave our audience with?</p>

<p>[01:00:57] It’s 100 years in the future, what do you want to be remembered for?     </p>

<p>[01:03:13] The Random Round.</p>]]>
  </content:encoded>
  <itunes:summary>
    <![CDATA[<p>MEMORABLE QUOTES <br>
[00:11:51] “..and then once you kind of clearly define exactly the outcome that you’re aiming for, it makes it a little bit easier to start breaking it down into chunks.”</p>

<p>[00:28:51] “ There are so many things that are outside of control. Just don’t even worry about those but focus on the things you can control.”</p>

<p>[00:38:28] “…having too much of it can be crippling but having a little bit can actually motivate you and push you to continue to grow your skillset which, ultimately, is beneficial to you and everybody around you.”</p>

<p>[00:40:15] “Fear is a powerful emotion. If you can wrestle it and have it push you from behind rather than block you, you learn whatever it is you’ve got to learn and improve and grow.“</p>

<p>[00:54:45] “As you provide more value and you’re reliable and you are providing good work, your influence will gradually grow.”</p>

<p>[01:02:12] “ I guess I’d want to be remembered for somebody who took on very difficult ambitious challenges where I knew that I had little possibility of succeeding but I still did it anyway.”</p>

<p>HIGHLIGHTS FROM THE SHOW</p>

<p>[00:00:51] Guest introduction.</p>

<p>[00:02:54] Can you tell us a little bit about where you grew up and what it was like there?</p>

<p>[00:03:42] When you were in high school, what did you think your future would look like?</p>

<p>[00:04:43] What was the journey like from there to now?</p>

<p>[00:06:39] What were some of the resources you used to help you figure out how to become a better learner?</p>

<p>[00:08:37] Can you define what deliberate practice means?</p>

<p>[00:10:18] How do we apply the concept?</p>

<p>[00:15:23] How would you define a mental model?   </p>

<p>[00:18:44] Which mental model would you say has had the biggest impact on the way you see the world?</p>

<p>[00:21:27] What does the problem-centric approach mean?</p>

<p>[00:25:47] Jeff talks about his secrets to getting multiple job offers.</p>

<p>[00:28:51] Did you ever feel emotionally invested in one given prospect?</p>

<p>[00:31:19] What would you say to someone scared of applying to job descriptions that look like they want the abilities of an entire team?</p>

<p>[00:33:51] What was common among all these interviews that you went for?</p>

<p>[00:36:21] What other nuanced things do you think a data scientist should really understand from school?</p>

<p>[00:37:52] What is your relationship with imposter syndrome like?</p>

<p>[00:40:15] Any words of encouragement for people trying to come back from an imposter syndrome?</p>

<p>[00:41:49] Talk to us about the importance of having a portfolio project.</p>

<p>[00:44:19] What are some of the biggest journalistic mistakes you’ve seen?</p>

<p>[00:45:21] Can you tell me how you would answer the “Tell me about yourself” question in an interview?</p>

<p>[00:47:20] If somebody wanted to a project using data from Spotify, what do you think would be a good project idea?</p>

<p>[00:49:20] How do you use deep learning to help you find dates here?</p>

<p>[00:51:21] What are some non-obvious skills that Data Scientists are missing that you think they should go and pick up?</p>

<p>[00:52:45] Do you keep a journal or anything like that?</p>

<p>[00:54:15] What tips can you share with data scientists for developing their leadership &amp;influence skills?</p>

<p>[00:58:52] What are some harsh truths about being a data scientist that you want to leave our audience with?</p>

<p>[01:00:57] It’s 100 years in the future, what do you want to be remembered for?     </p>

<p>[01:03:13] The Random Round.</p>]]>
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