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    <title>Teaching Python - Episodes Tagged with “Stem Education”</title>
    <link>https://www.teachingpython.fm/tags/stem%20education</link>
    <pubDate>Mon, 22 Jun 2026 00:00:00 -0400</pubDate>
    <description>Teaching Python is a podcast about Python programming, computer science education, AI literacy, software development, cloud computing, cybersecurity, data, and how people learn technical skills. Hosted by Kelly Schuster-Paredes, Sean Tibor, and Julian Sequeira, the show is for educators, developers, technology leaders, and lifelong learners who want to better understand how Python connects to the wider world of computing. Episodes explore not only how people learn to code, but also how they build technical judgment, understand systems, evaluate AI-generated code, work with data, think about security, and move from beginner programming into real-world software development. About the Hosts Kelly Schuster-Paredes is a teacher who codes whose work has expanded from classroom computer science into AI strategy, curriculum design, professional learning, educational technology, and responsible technology adoption. Her background in Python and computer science education shapes her focus on learning, AI literacy, computational thinking, and what people need to understand in an AI-shaped world. Sean Tibor is Vice President of Infrastructure and Cloud at Pfizer and a former computer science teacher. He brings expertise in cloud computing, infrastructure, engineering operations, and technical leadership, connecting what people learn about computing with how large-scale systems are actually built, operated, secured, and maintained. Julian Sequiera is a technologist, Fractional CTO, and Senior Program Manager with more than 20 years of experience in infrastructure, cloud, engineering operations, and large-scale technology programs. He is also the co-founder of PyBites, a Python learning platform and community that has helped thousands of developers improve their Python and software development skills. What We Cover Python Programming and Computer Science Education: Learning Python, teaching programming, computational thinking, debugging, code literacy, and helping beginners build strong mental models. AI and AI Literacy: AI-assisted programming, evaluating AI-generated code, responsible AI use, human judgment, and what learners still need to understand when AI can produce code. Cloud, Infrastructure, and Cybersecurity: Systems, networks, deployment, security, reliability, architecture, and the operational side of software. Data and Software Engineering: APIs, databases, testing, maintainability, version control, software design, and moving from simple scripts to real-world applications. Learning and Technical Growth: How people learn difficult technical concepts, get unstuck, build confidence, and develop the judgment needed to use technology well. Expert Interviews: Conversations with educators, developers, engineers, researchers, technology leaders, and others shaping the future of computing and technical education. Teaching Python remains grounded in Python, but the conversation extends beyond syntax. The podcast explores the knowledge, skills, systems, and judgment people need to learn, build, and make responsible decisions with technology.</description>
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    <itunes:subtitle>We're two computer science educators learning and teaching Python</itunes:subtitle>
    <itunes:author>Sean Tibor and Kelly Paredes</itunes:author>
    <itunes:summary>Teaching Python is a podcast about Python programming, computer science education, AI literacy, software development, cloud computing, cybersecurity, data, and how people learn technical skills. Hosted by Kelly Schuster-Paredes, Sean Tibor, and Julian Sequeira, the show is for educators, developers, technology leaders, and lifelong learners who want to better understand how Python connects to the wider world of computing. Episodes explore not only how people learn to code, but also how they build technical judgment, understand systems, evaluate AI-generated code, work with data, think about security, and move from beginner programming into real-world software development. About the Hosts Kelly Schuster-Paredes is a teacher who codes whose work has expanded from classroom computer science into AI strategy, curriculum design, professional learning, educational technology, and responsible technology adoption. Her background in Python and computer science education shapes her focus on learning, AI literacy, computational thinking, and what people need to understand in an AI-shaped world. Sean Tibor is Vice President of Infrastructure and Cloud at Pfizer and a former computer science teacher. He brings expertise in cloud computing, infrastructure, engineering operations, and technical leadership, connecting what people learn about computing with how large-scale systems are actually built, operated, secured, and maintained. Julian Sequiera is a technologist, Fractional CTO, and Senior Program Manager with more than 20 years of experience in infrastructure, cloud, engineering operations, and large-scale technology programs. He is also the co-founder of PyBites, a Python learning platform and community that has helped thousands of developers improve their Python and software development skills. What We Cover Python Programming and Computer Science Education: Learning Python, teaching programming, computational thinking, debugging, code literacy, and helping beginners build strong mental models. AI and AI Literacy: AI-assisted programming, evaluating AI-generated code, responsible AI use, human judgment, and what learners still need to understand when AI can produce code. Cloud, Infrastructure, and Cybersecurity: Systems, networks, deployment, security, reliability, architecture, and the operational side of software. Data and Software Engineering: APIs, databases, testing, maintainability, version control, software design, and moving from simple scripts to real-world applications. Learning and Technical Growth: How people learn difficult technical concepts, get unstuck, build confidence, and develop the judgment needed to use technology well. Expert Interviews: Conversations with educators, developers, engineers, researchers, technology leaders, and others shaping the future of computing and technical education. Teaching Python remains grounded in Python, but the conversation extends beyond syntax. The podcast explores the knowledge, skills, systems, and judgment people need to learn, build, and make responsible decisions with technology.</itunes:summary>
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    <itunes:keywords>Python, Python programming, learn Python, teaching Python, computer science education, coding education, programming for beginners, Python for beginners, computational thinking, code literacy, debugging, software development, software engineering, data science, artificial intelligence, AI literacy, AI-assisted coding, generative AI, machine learning, cybersecurity, cloud computing, cloud infrastructure, APIs, databases, systems thinking, technical education, STEM education, educational technology, edtech, curriculum design, instructional design, professional learning, teacher professional development, coding for students, computer science curriculum, physical computing, robotics, responsible AI, digital literacy, data literacy, technology leadership, developer education, technical coaching, lifelong learning, learning to code, teaching programming, real-world programming, coding with AI, Python podcast, computer science podcast, technology education podcast, programming podcast</itunes:keywords>
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      <itunes:name>Sean Tibor and Kelly Paredes</itunes:name>
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<item>
  <title>Episode 159: Big Lessons from Small Models with Gwyneth Peña‑Siguenza</title>
  <link>https://www.teachingpython.fm/159</link>
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  <pubDate>Mon, 22 Jun 2026 00:00:00 -0400</pubDate>
  <author>Sean Tibor and Kelly Paredes</author>
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  <itunes:episode>159</itunes:episode>
  <itunes:title>Big Lessons from Small Models with Gwyneth Peña‑Siguenza</itunes:title>
  <itunes:episodeType>full</itunes:episodeType>
  <itunes:author>Sean Tibor and Kelly Paredes</itunes:author>
  <itunes:subtitle>Small language models may be the best way to learn AI. Microsoft Cloud Advocate Gwyneth Peña-Sigüenza joins us to discuss Python, cloud computing, security, and why the limitations of smaller models can build stronger developers.</itunes:subtitle>
  <itunes:duration>56:15</itunes:duration>
  <itunes:explicit>no</itunes:explicit>
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  <description>&lt;p&gt;What can small language models teach us that the largest AI models cannot?&lt;/p&gt;

&lt;p&gt;Kelly and Julian are joined by Microsoft Cloud Advocate Gwyneth Peña-Sigüenza to explore why working with small language models (SLMs) may be one of the best ways to understand AI. Rather than relying on increasingly capable models that hide complexity, Gwyneth argues that constraints build stronger fundamentals. From prompt engineering and context management to deployment and security, SLMs force learners to think more carefully about how AI actually works.&lt;/p&gt;

&lt;p&gt;The conversation extends beyond AI models into learning itself. Gwyneth shares her self-taught journey from growing up on a remote farm in Ecuador with limited internet access to becoming a Microsoft Cloud Advocate and creator of the Learn to Cloud platform. Along the way, the group discusses productive struggle, mentorship, cloud engineering, Python, security, and what educators should prioritize as AI becomes part of every student's learning experience.&lt;/p&gt;

&lt;p&gt;The episode closes with a thoughtful discussion about AI dependency, judgment, and whether we would actually flip the switch and turn AI off if given the choice.&lt;/p&gt;

&lt;h2&gt;Show Notes&lt;/h2&gt;

&lt;h3&gt;Wins of the Week&lt;/h3&gt;

&lt;ul&gt;
&lt;li&gt;  Gwyneth celebrates the New York Knicks reaching the NBA Finals after more than 50 years.&lt;/li&gt;
&lt;li&gt;  Julian shares that he has accepted a new role as a Fractional CTO.&lt;/li&gt;
&lt;li&gt;  Kelly reflects on taking her first real vacation in over a year—and how stepping away from work sparked unexpected ideas.&lt;/li&gt;
&lt;/ul&gt;

&lt;h3&gt;Small Language Models&lt;/h3&gt;

&lt;ul&gt;
&lt;li&gt;  Why SLMs are valuable teaching tools&lt;/li&gt;
&lt;li&gt;  Learning prompt engineering through constraints&lt;/li&gt;
&lt;li&gt;  Running models locally on everyday hardware&lt;/li&gt;
&lt;li&gt;  When local AI makes sense for classrooms&lt;/li&gt;
&lt;li&gt;  Understanding tokens, context windows, and model limitations&lt;/li&gt;
&lt;li&gt;  Why bigger models can sometimes hide important lessons&lt;/li&gt;
&lt;/ul&gt;

&lt;h3&gt;Learning Through Constraints&lt;/h3&gt;

&lt;ul&gt;
&lt;li&gt;  Learning to drive in an old manual pickup truck as a metaphor for learning AI fundamentals&lt;/li&gt;
&lt;li&gt;  Why difficult learning experiences often create lasting understanding&lt;/li&gt;
&lt;li&gt;  Building strong habits before relying on more capable tools&lt;/li&gt;
&lt;li&gt;  Consistency versus constantly chasing the newest resource&lt;/li&gt;
&lt;/ul&gt;

&lt;h3&gt;Self-Taught Learning&lt;/h3&gt;

&lt;ul&gt;
&lt;li&gt;  Growing up without reliable internet in rural Ecuador&lt;/li&gt;
&lt;li&gt;  Downloading YouTube playlists to learn programming offline&lt;/li&gt;
&lt;li&gt;  Developing discipline through limited access&lt;/li&gt;
&lt;li&gt;  The value of repetition and focused practice&lt;/li&gt;
&lt;li&gt;  Why mentorship accelerates learning&lt;/li&gt;
&lt;/ul&gt;

&lt;h3&gt;Python Journey&lt;/h3&gt;

&lt;ul&gt;
&lt;li&gt;  Transitioning from cloud engineering to Python advocacy&lt;/li&gt;
&lt;li&gt;  Learning Python beyond scripting&lt;/li&gt;
&lt;li&gt;  Discovering what "Pythonic" really means&lt;/li&gt;
&lt;li&gt;  Wrestling with list comprehensions and other advanced syntax&lt;/li&gt;
&lt;li&gt;  Favorite learning resources:

&lt;ul&gt;
&lt;li&gt;  &lt;em&gt;Fluent Python&lt;/em&gt;&lt;/li&gt;
&lt;li&gt;  &lt;em&gt;Effective Python&lt;/em&gt;&lt;/li&gt;
&lt;/ul&gt;&lt;/li&gt;
&lt;/ul&gt;

&lt;h3&gt;Learn to Cloud&lt;/h3&gt;

&lt;ul&gt;
&lt;li&gt;  Building an open-source cloud engineering curriculum&lt;/li&gt;
&lt;li&gt;  Hands-on labs and automated verification&lt;/li&gt;
&lt;li&gt;  AI-assisted assessment&lt;/li&gt;
&lt;li&gt;  Supporting self-taught learners around the world&lt;/li&gt;
&lt;li&gt;  Creating accessible technical education&lt;/li&gt;
&lt;/ul&gt;

&lt;h3&gt;Cloud, AI, and Security&lt;/h3&gt;

&lt;ul&gt;
&lt;li&gt;  Deploying AI applications to the cloud&lt;/li&gt;
&lt;li&gt;  Containers, virtual machines, and serverless deployments&lt;/li&gt;
&lt;li&gt;  Why operations and security deserve more classroom attention&lt;/li&gt;
&lt;li&gt;  Introducing secure development practices early&lt;/li&gt;
&lt;li&gt;  The importance of authentication, secrets management, and responsible deployment&lt;/li&gt;
&lt;/ul&gt;

&lt;h3&gt;Teaching in the AI Era&lt;/h3&gt;

&lt;ul&gt;
&lt;li&gt;  Helping students understand how AI works instead of simply using it&lt;/li&gt;
&lt;li&gt;  Why productive struggle still matters&lt;/li&gt;
&lt;li&gt;  The changing role of educators&lt;/li&gt;
&lt;li&gt;  Balancing AI assistance with independent thinking&lt;/li&gt;
&lt;li&gt;  Preparing students for a future where AI is always available&lt;/li&gt;
&lt;/ul&gt;

&lt;h3&gt;Final Thoughts&lt;/h3&gt;

&lt;ul&gt;
&lt;li&gt;  AI dependency versus capability&lt;/li&gt;
&lt;li&gt;  Judgment as the skill that matters most&lt;/li&gt;
&lt;li&gt;  Human connection in an AI-driven world&lt;/li&gt;
&lt;li&gt;  Would we actually turn AI off?&lt;/li&gt;
&lt;li&gt;  Finding balance between technological progress and intentional learning &lt;/li&gt;
&lt;/ul&gt;
</description>
  <itunes:keywords>Education, Technology, Programming, Python, Coding, STEM Education, Tech Learning, Digital Literacy, Tech Tutorials, Python Programming, Computer Science, EdTech, Coding for Beginners, DIY Projects, Interactive Learning, Software Development, Teaching Technology</itunes:keywords>
  <content:encoded>
    <![CDATA[<p>What can small language models teach us that the largest AI models cannot?</p>

<p>Kelly and Julian are joined by Microsoft Cloud Advocate Gwyneth Peña-Sigüenza to explore why working with small language models (SLMs) may be one of the best ways to understand AI. Rather than relying on increasingly capable models that hide complexity, Gwyneth argues that constraints build stronger fundamentals. From prompt engineering and context management to deployment and security, SLMs force learners to think more carefully about how AI actually works.</p>

<p>The conversation extends beyond AI models into learning itself. Gwyneth shares her self-taught journey from growing up on a remote farm in Ecuador with limited internet access to becoming a Microsoft Cloud Advocate and creator of the Learn to Cloud platform. Along the way, the group discusses productive struggle, mentorship, cloud engineering, Python, security, and what educators should prioritize as AI becomes part of every student's learning experience.</p>

<p>The episode closes with a thoughtful discussion about AI dependency, judgment, and whether we would actually flip the switch and turn AI off if given the choice.</p>

<h2>Show Notes</h2>

<h3>Wins of the Week</h3>

<ul>
<li>  Gwyneth celebrates the New York Knicks reaching the NBA Finals after more than 50 years.</li>
<li>  Julian shares that he has accepted a new role as a Fractional CTO.</li>
<li>  Kelly reflects on taking her first real vacation in over a year—and how stepping away from work sparked unexpected ideas.</li>
</ul>

<h3>Small Language Models</h3>

<ul>
<li>  Why SLMs are valuable teaching tools</li>
<li>  Learning prompt engineering through constraints</li>
<li>  Running models locally on everyday hardware</li>
<li>  When local AI makes sense for classrooms</li>
<li>  Understanding tokens, context windows, and model limitations</li>
<li>  Why bigger models can sometimes hide important lessons</li>
</ul>

<h3>Learning Through Constraints</h3>

<ul>
<li>  Learning to drive in an old manual pickup truck as a metaphor for learning AI fundamentals</li>
<li>  Why difficult learning experiences often create lasting understanding</li>
<li>  Building strong habits before relying on more capable tools</li>
<li>  Consistency versus constantly chasing the newest resource</li>
</ul>

<h3>Self-Taught Learning</h3>

<ul>
<li>  Growing up without reliable internet in rural Ecuador</li>
<li>  Downloading YouTube playlists to learn programming offline</li>
<li>  Developing discipline through limited access</li>
<li>  The value of repetition and focused practice</li>
<li>  Why mentorship accelerates learning</li>
</ul>

<h3>Python Journey</h3>

<ul>
<li>  Transitioning from cloud engineering to Python advocacy</li>
<li>  Learning Python beyond scripting</li>
<li>  Discovering what "Pythonic" really means</li>
<li>  Wrestling with list comprehensions and other advanced syntax</li>
<li>  Favorite learning resources:

<ul>
<li>  <em>Fluent Python</em></li>
<li>  <em>Effective Python</em></li>
</ul></li>
</ul>

<h3>Learn to Cloud</h3>

<ul>
<li>  Building an open-source cloud engineering curriculum</li>
<li>  Hands-on labs and automated verification</li>
<li>  AI-assisted assessment</li>
<li>  Supporting self-taught learners around the world</li>
<li>  Creating accessible technical education</li>
</ul>

<h3>Cloud, AI, and Security</h3>

<ul>
<li>  Deploying AI applications to the cloud</li>
<li>  Containers, virtual machines, and serverless deployments</li>
<li>  Why operations and security deserve more classroom attention</li>
<li>  Introducing secure development practices early</li>
<li>  The importance of authentication, secrets management, and responsible deployment</li>
</ul>

<h3>Teaching in the AI Era</h3>

<ul>
<li>  Helping students understand how AI works instead of simply using it</li>
<li>  Why productive struggle still matters</li>
<li>  The changing role of educators</li>
<li>  Balancing AI assistance with independent thinking</li>
<li>  Preparing students for a future where AI is always available</li>
</ul>

<h3>Final Thoughts</h3>

<ul>
<li>  AI dependency versus capability</li>
<li>  Judgment as the skill that matters most</li>
<li>  Human connection in an AI-driven world</li>
<li>  Would we actually turn AI off?</li>
<li>  Finding balance between technological progress and intentional learning</li>
</ul><p><a rel="payment" href="https://www.patreon.com/teachingpython">Support Teaching Python</a></p>]]>
  </content:encoded>
  <itunes:summary>
    <![CDATA[<p>What can small language models teach us that the largest AI models cannot?</p>

<p>Kelly and Julian are joined by Microsoft Cloud Advocate Gwyneth Peña-Sigüenza to explore why working with small language models (SLMs) may be one of the best ways to understand AI. Rather than relying on increasingly capable models that hide complexity, Gwyneth argues that constraints build stronger fundamentals. From prompt engineering and context management to deployment and security, SLMs force learners to think more carefully about how AI actually works.</p>

<p>The conversation extends beyond AI models into learning itself. Gwyneth shares her self-taught journey from growing up on a remote farm in Ecuador with limited internet access to becoming a Microsoft Cloud Advocate and creator of the Learn to Cloud platform. Along the way, the group discusses productive struggle, mentorship, cloud engineering, Python, security, and what educators should prioritize as AI becomes part of every student's learning experience.</p>

<p>The episode closes with a thoughtful discussion about AI dependency, judgment, and whether we would actually flip the switch and turn AI off if given the choice.</p>

<h2>Show Notes</h2>

<h3>Wins of the Week</h3>

<ul>
<li>  Gwyneth celebrates the New York Knicks reaching the NBA Finals after more than 50 years.</li>
<li>  Julian shares that he has accepted a new role as a Fractional CTO.</li>
<li>  Kelly reflects on taking her first real vacation in over a year—and how stepping away from work sparked unexpected ideas.</li>
</ul>

<h3>Small Language Models</h3>

<ul>
<li>  Why SLMs are valuable teaching tools</li>
<li>  Learning prompt engineering through constraints</li>
<li>  Running models locally on everyday hardware</li>
<li>  When local AI makes sense for classrooms</li>
<li>  Understanding tokens, context windows, and model limitations</li>
<li>  Why bigger models can sometimes hide important lessons</li>
</ul>

<h3>Learning Through Constraints</h3>

<ul>
<li>  Learning to drive in an old manual pickup truck as a metaphor for learning AI fundamentals</li>
<li>  Why difficult learning experiences often create lasting understanding</li>
<li>  Building strong habits before relying on more capable tools</li>
<li>  Consistency versus constantly chasing the newest resource</li>
</ul>

<h3>Self-Taught Learning</h3>

<ul>
<li>  Growing up without reliable internet in rural Ecuador</li>
<li>  Downloading YouTube playlists to learn programming offline</li>
<li>  Developing discipline through limited access</li>
<li>  The value of repetition and focused practice</li>
<li>  Why mentorship accelerates learning</li>
</ul>

<h3>Python Journey</h3>

<ul>
<li>  Transitioning from cloud engineering to Python advocacy</li>
<li>  Learning Python beyond scripting</li>
<li>  Discovering what "Pythonic" really means</li>
<li>  Wrestling with list comprehensions and other advanced syntax</li>
<li>  Favorite learning resources:

<ul>
<li>  <em>Fluent Python</em></li>
<li>  <em>Effective Python</em></li>
</ul></li>
</ul>

<h3>Learn to Cloud</h3>

<ul>
<li>  Building an open-source cloud engineering curriculum</li>
<li>  Hands-on labs and automated verification</li>
<li>  AI-assisted assessment</li>
<li>  Supporting self-taught learners around the world</li>
<li>  Creating accessible technical education</li>
</ul>

<h3>Cloud, AI, and Security</h3>

<ul>
<li>  Deploying AI applications to the cloud</li>
<li>  Containers, virtual machines, and serverless deployments</li>
<li>  Why operations and security deserve more classroom attention</li>
<li>  Introducing secure development practices early</li>
<li>  The importance of authentication, secrets management, and responsible deployment</li>
</ul>

<h3>Teaching in the AI Era</h3>

<ul>
<li>  Helping students understand how AI works instead of simply using it</li>
<li>  Why productive struggle still matters</li>
<li>  The changing role of educators</li>
<li>  Balancing AI assistance with independent thinking</li>
<li>  Preparing students for a future where AI is always available</li>
</ul>

<h3>Final Thoughts</h3>

<ul>
<li>  AI dependency versus capability</li>
<li>  Judgment as the skill that matters most</li>
<li>  Human connection in an AI-driven world</li>
<li>  Would we actually turn AI off?</li>
<li>  Finding balance between technological progress and intentional learning</li>
</ul><p><a rel="payment" href="https://www.patreon.com/teachingpython">Support Teaching Python</a></p>]]>
  </itunes:summary>
</item>
<item>
  <title>Episode 110: CircuitPython with Kattni Rembor</title>
  <link>https://www.teachingpython.fm/110</link>
  <guid isPermaLink="false">f00be956-0fe0-46ab-9d44-44e4d2491d66</guid>
  <pubDate>Fri, 23 Jun 2023 08:00:00 -0400</pubDate>
  <author>Sean Tibor and Kelly Paredes</author>
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  <itunes:episode>110</itunes:episode>
  <itunes:title>CircuitPython with Kattni Rembor</itunes:title>
  <itunes:episodeType>full</itunes:episodeType>
  <itunes:author>Sean Tibor and Kelly Paredes</itunes:author>
  <itunes:subtitle>It's no secret that we're huge fans of CircuitPython and the plethora of boards from Adafruit that make learning more tactile and colorful. We chat with friend of the show Kattni Rembor, a Creative Engineer sponsored by Adafruit to talk about her work with CircuitPython and the vibrant community that has sprung up around it.</itunes:subtitle>
  <itunes:duration>1:04:31</itunes:duration>
  <itunes:explicit>no</itunes:explicit>
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  <description>&lt;h2&gt;Show Notes&lt;/h2&gt;

&lt;h3&gt;Introduction&lt;/h3&gt;

&lt;ul&gt;
&lt;li&gt;Welcome to this week's episode, entirely devoted to CircuitPython. We're excited to have Kattni Rembor from Adafruit as our special guest, who has contributed extensively to the CircuitPython platform, from beginner guides to advanced projects.&lt;/li&gt;
&lt;/ul&gt;

&lt;h3&gt;Kattni's Win of the Week&lt;/h3&gt;

&lt;ul&gt;
&lt;li&gt;Kattni shares her current project, a guide for creating a keyboard key switch with NeoPixels underneath. Each key press generates a random LED color.&lt;/li&gt;
&lt;/ul&gt;

&lt;h3&gt;Our Wins of the Week&lt;/h3&gt;

&lt;ul&gt;
&lt;li&gt;Kelly Schuster-Paredes, currently on vacation, shares her achievement of resting for two consecutive minutes. &lt;/li&gt;
&lt;li&gt;Sean shares his experience using the Marp tool for presentations but admits to time management struggles.&lt;/li&gt;
&lt;/ul&gt;

&lt;h3&gt;CircuitPython Introduction&lt;/h3&gt;

&lt;ul&gt;
&lt;li&gt;We delve into CircuitPython, a version of Python designed for microcontrollers. Created for beginners and educational purposes, it provides a unique approach to learning Python.&lt;/li&gt;
&lt;/ul&gt;

&lt;h3&gt;CircuitPython Applications&lt;/h3&gt;

&lt;ul&gt;
&lt;li&gt;Kattni enlightens us on the vast applications of CircuitPython, ranging from environmental sensing to assistive technologies for people with disabilities.&lt;/li&gt;
&lt;/ul&gt;

&lt;h3&gt;CircuitPython Capabilities&lt;/h3&gt;

&lt;ul&gt;
&lt;li&gt;We discuss how CircuitPython simplifies complex tasks, fostering creativity and making tasks like LED blinking quite straightforward.&lt;/li&gt;
&lt;/ul&gt;

&lt;h3&gt;CircuitPython Boards&lt;/h3&gt;

&lt;ul&gt;
&lt;li&gt;At the time of recording, there are 413 boards compatible with CircuitPython available at circuitpython.org. We also discuss Adafruit's educational pricing and discounts.&lt;/li&gt;
&lt;/ul&gt;

&lt;h3&gt;Top CircuitPython Boards&lt;/h3&gt;

&lt;ul&gt;
&lt;li&gt;We list our top five favorite boards for education, ease of use, and fun projects, including Blue fruit and Circuit Playground Express.&lt;/li&gt;
&lt;/ul&gt;

&lt;h3&gt;Getting Started with CircuitPython&lt;/h3&gt;

&lt;ul&gt;
&lt;li&gt;Starting with CircuitPython can be challenging for beginners. We discuss some common issues and solutions, like copying required libraries immediately after importing.&lt;/li&gt;
&lt;/ul&gt;

&lt;h3&gt;CircuitPython in the Classroom&lt;/h3&gt;

&lt;ul&gt;
&lt;li&gt;We highlight the immense possibilities of CircuitPython in educational settings and encourage educators to explore its potential.&lt;/li&gt;
&lt;/ul&gt;

&lt;h3&gt;Connect with Kattni Rembor&lt;/h3&gt;

&lt;ul&gt;
&lt;li&gt;You can follow Kattni Rembor's projects on the Adafruit Learning System and on social media platforms like Mastodon.&lt;/li&gt;
&lt;/ul&gt;

&lt;h3&gt;Live Streaming Announcement&lt;/h3&gt;

&lt;ul&gt;
&lt;li&gt;Kelly announces the "Summer of Streaming," aiming to live stream every Wednesday at three.&lt;/li&gt;
&lt;/ul&gt;

&lt;h3&gt;Closing Remarks&lt;/h3&gt;

&lt;ul&gt;
&lt;li&gt;We wrap up the episode with Kattni expressing her enjoyment in discussing CircuitPython and her excitement for future projects. Sean and Kelly sign off, looking forward to the next episode.
Special Guest: Kattni Rembor.&lt;/li&gt;
&lt;/ul&gt;
</description>
  <itunes:keywords>CircuitPython, Adafruit, Kattni Rembor, Microcontrollers, Python for beginners, Educational Python, Python coding, Coding education</itunes:keywords>
  <content:encoded>
    <![CDATA[<h2>Show Notes</h2>

<h3>Introduction</h3>

<ul>
<li>Welcome to this week's episode, entirely devoted to CircuitPython. We're excited to have Kattni Rembor from Adafruit as our special guest, who has contributed extensively to the CircuitPython platform, from beginner guides to advanced projects.</li>
</ul>

<h3>Kattni's Win of the Week</h3>

<ul>
<li>Kattni shares her current project, a guide for creating a keyboard key switch with NeoPixels underneath. Each key press generates a random LED color.</li>
</ul>

<h3>Our Wins of the Week</h3>

<ul>
<li>Kelly Schuster-Paredes, currently on vacation, shares her achievement of resting for two consecutive minutes. </li>
<li>Sean shares his experience using the Marp tool for presentations but admits to time management struggles.</li>
</ul>

<h3>CircuitPython Introduction</h3>

<ul>
<li>We delve into CircuitPython, a version of Python designed for microcontrollers. Created for beginners and educational purposes, it provides a unique approach to learning Python.</li>
</ul>

<h3>CircuitPython Applications</h3>

<ul>
<li>Kattni enlightens us on the vast applications of CircuitPython, ranging from environmental sensing to assistive technologies for people with disabilities.</li>
</ul>

<h3>CircuitPython Capabilities</h3>

<ul>
<li>We discuss how CircuitPython simplifies complex tasks, fostering creativity and making tasks like LED blinking quite straightforward.</li>
</ul>

<h3>CircuitPython Boards</h3>

<ul>
<li>At the time of recording, there are 413 boards compatible with CircuitPython available at circuitpython.org. We also discuss Adafruit's educational pricing and discounts.</li>
</ul>

<h3>Top CircuitPython Boards</h3>

<ul>
<li>We list our top five favorite boards for education, ease of use, and fun projects, including Blue fruit and Circuit Playground Express.</li>
</ul>

<h3>Getting Started with CircuitPython</h3>

<ul>
<li>Starting with CircuitPython can be challenging for beginners. We discuss some common issues and solutions, like copying required libraries immediately after importing.</li>
</ul>

<h3>CircuitPython in the Classroom</h3>

<ul>
<li>We highlight the immense possibilities of CircuitPython in educational settings and encourage educators to explore its potential.</li>
</ul>

<h3>Connect with Kattni Rembor</h3>

<ul>
<li>You can follow Kattni Rembor's projects on the Adafruit Learning System and on social media platforms like Mastodon.</li>
</ul>

<h3>Live Streaming Announcement</h3>

<ul>
<li>Kelly announces the "Summer of Streaming," aiming to live stream every Wednesday at three.</li>
</ul>

<h3>Closing Remarks</h3>

<ul>
<li>We wrap up the episode with Kattni expressing her enjoyment in discussing CircuitPython and her excitement for future projects. Sean and Kelly sign off, looking forward to the next episode.</li>
</ul><p>Special Guest: Kattni Rembor.</p><p><a rel="payment" href="https://www.patreon.com/teachingpython">Support Teaching Python</a></p>]]>
  </content:encoded>
  <itunes:summary>
    <![CDATA[<h2>Show Notes</h2>

<h3>Introduction</h3>

<ul>
<li>Welcome to this week's episode, entirely devoted to CircuitPython. We're excited to have Kattni Rembor from Adafruit as our special guest, who has contributed extensively to the CircuitPython platform, from beginner guides to advanced projects.</li>
</ul>

<h3>Kattni's Win of the Week</h3>

<ul>
<li>Kattni shares her current project, a guide for creating a keyboard key switch with NeoPixels underneath. Each key press generates a random LED color.</li>
</ul>

<h3>Our Wins of the Week</h3>

<ul>
<li>Kelly Schuster-Paredes, currently on vacation, shares her achievement of resting for two consecutive minutes. </li>
<li>Sean shares his experience using the Marp tool for presentations but admits to time management struggles.</li>
</ul>

<h3>CircuitPython Introduction</h3>

<ul>
<li>We delve into CircuitPython, a version of Python designed for microcontrollers. Created for beginners and educational purposes, it provides a unique approach to learning Python.</li>
</ul>

<h3>CircuitPython Applications</h3>

<ul>
<li>Kattni enlightens us on the vast applications of CircuitPython, ranging from environmental sensing to assistive technologies for people with disabilities.</li>
</ul>

<h3>CircuitPython Capabilities</h3>

<ul>
<li>We discuss how CircuitPython simplifies complex tasks, fostering creativity and making tasks like LED blinking quite straightforward.</li>
</ul>

<h3>CircuitPython Boards</h3>

<ul>
<li>At the time of recording, there are 413 boards compatible with CircuitPython available at circuitpython.org. We also discuss Adafruit's educational pricing and discounts.</li>
</ul>

<h3>Top CircuitPython Boards</h3>

<ul>
<li>We list our top five favorite boards for education, ease of use, and fun projects, including Blue fruit and Circuit Playground Express.</li>
</ul>

<h3>Getting Started with CircuitPython</h3>

<ul>
<li>Starting with CircuitPython can be challenging for beginners. We discuss some common issues and solutions, like copying required libraries immediately after importing.</li>
</ul>

<h3>CircuitPython in the Classroom</h3>

<ul>
<li>We highlight the immense possibilities of CircuitPython in educational settings and encourage educators to explore its potential.</li>
</ul>

<h3>Connect with Kattni Rembor</h3>

<ul>
<li>You can follow Kattni Rembor's projects on the Adafruit Learning System and on social media platforms like Mastodon.</li>
</ul>

<h3>Live Streaming Announcement</h3>

<ul>
<li>Kelly announces the "Summer of Streaming," aiming to live stream every Wednesday at three.</li>
</ul>

<h3>Closing Remarks</h3>

<ul>
<li>We wrap up the episode with Kattni expressing her enjoyment in discussing CircuitPython and her excitement for future projects. Sean and Kelly sign off, looking forward to the next episode.</li>
</ul><p>Special Guest: Kattni Rembor.</p><p><a rel="payment" href="https://www.patreon.com/teachingpython">Support Teaching Python</a></p>]]>
  </itunes:summary>
</item>
  </channel>
</rss>
