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    <title>Teaching Python - Episodes Tagged with “Python Programming”</title>
    <link>https://www.teachingpython.fm/tags/python%20programming</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>
    <itunes:owner>
      <itunes:name>Sean Tibor and Kelly Paredes</itunes:name>
      <itunes:email>sean.tibor@gmail.com</itunes:email>
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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 142: Middle School Magic: Integrating AI, Data Science, and Computational Thinking with Kelly Powers</title>
  <link>https://www.teachingpython.fm/142</link>
  <guid isPermaLink="false">28ac0fd5-3b5f-46c2-9dae-56480c23a1d2</guid>
  <pubDate>Sun, 22 Dec 2024 14:00:00 -0500</pubDate>
  <author>Sean Tibor and Kelly Paredes</author>
  <enclosure url="https://aphid.fireside.fm/d/1437767933/c8ea6bdf-0c80-46e7-a00a-639d7dc2be91/28ac0fd5-3b5f-46c2-9dae-56480c23a1d2.mp3" length="58068834" type="audio/mpeg"/>
  <itunes:episode>142</itunes:episode>
  <itunes:title>Middle School Magic: Integrating AI, Data Science, and Computational Thinking with Kelly Powers</itunes:title>
  <itunes:episodeType>full</itunes:episodeType>
  <itunes:author>Sean Tibor and Kelly Paredes</itunes:author>
  <itunes:subtitle>In Episode 142 of Teaching Python, hosts Sean Tibor and Kelly Schuster-Paredes converse with Kelly Powers, a middle school educator and curriculum designer. They delve into a myriad of engaging topics, including the intricacies of teaching computational thinking skills, the integration of AI and data science into the middle school curriculum, and the unique challenges and joys of teaching middle school students. The episode is packed with insights on fostering creativity, collaboration, and critical thinking in the classroom. Don't miss this enlightening discussion for educators and tech enthusiasts alike!</itunes:subtitle>
  <itunes:duration>1:00:01</itunes:duration>
  <itunes:explicit>no</itunes:explicit>
  <itunes:image href="https://media24.fireside.fm/file/fireside-images-2024/podcasts/images/c/c8ea6bdf-0c80-46e7-a00a-639d7dc2be91/episodes/2/28ac0fd5-3b5f-46c2-9dae-56480c23a1d2/cover.jpg?v=1"/>
  <description>&lt;p&gt;In Episode 142 of Teaching Python, hosts Sean Tibor and Kelly Schuster-Paredes are joined by Kelly Powers, a fellow middle school educator and curriculum designer, to explore the dynamic world of middle school instruction. As a passionate advocate for computational thinking, Powers shares valuable insights on introducing students to the concepts of AI, data science, and cybersecurity in a way that is both rigorous and joyful.&lt;/p&gt;

&lt;h2&gt;Topics Covered&lt;/h2&gt;

&lt;ul&gt;
&lt;li&gt;&lt;strong&gt;Engaging Middle School Students&lt;/strong&gt;: Strategies for capturing and maintaining student interest.&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Creativity and Collaboration&lt;/strong&gt;: How to foster a collaborative environment that inspires creativity.&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Core Computational Concepts&lt;/strong&gt;: Real-world applications that make these concepts accessible and interesting.&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Data Science Projects&lt;/strong&gt;: Practical advice on integrating data science into your curriculum.&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Generative AI Ethics&lt;/strong&gt;: Discussing the ethical use of AI in education.&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Python as a Teaching Tool&lt;/strong&gt;: Exploring the versatility of Python for various projects.&lt;/li&gt;
&lt;/ul&gt;

&lt;h2&gt;Key Takeaways&lt;/h2&gt;

&lt;ul&gt;
&lt;li&gt;&lt;strong&gt;&lt;em&gt;Integrating Computational Thinking Skills&lt;/em&gt;&lt;/strong&gt;: Tips on how to weave these skills into everyday classroom routines.&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;&lt;em&gt;Teamwork and Communication&lt;/em&gt;&lt;/strong&gt;: The importance of teamwork and effective communication in coding projects.&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;&lt;em&gt;Engaging Lessons with Python&lt;/em&gt;&lt;/strong&gt;: How Python can be used to create engaging and meaningful projects for students.&lt;/li&gt;
&lt;/ul&gt;

&lt;h2&gt;About Kelly Powers&lt;/h2&gt;

&lt;p&gt;Kelly Powers transitioned from the business world to education, bringing a fresh perspective on teaching computational thinking. She offers invaluable insights into making rigorous and joyful learning experiences for middle school students.&lt;/p&gt;

&lt;p&gt;Whether you are an experienced teacher or new to the field, this episode is packed with actionable ideas and inspirational moments that will help you create a more engaging and effective learning environment.&lt;/p&gt;

&lt;p&gt;Tune in for a lively conversation that celebrates the magic of middle school teaching and the endless possibilities of computer science education.&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Listen to the episode&lt;/strong&gt;: &lt;a href="https://www.teachingpython.fm/142" rel="nofollow noopener"&gt;Teaching Python Podcast&lt;/a&gt;&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Follow us on Social Media&lt;/strong&gt;:&lt;/p&gt;

&lt;ul&gt;
&lt;li&gt;&lt;a href="https://twitter.com/teachingpython" rel="nofollow noopener"&gt;Twitter&lt;/a&gt;&lt;/li&gt;
&lt;li&gt;&lt;a href="https://www.facebook.com/teachingpython" rel="nofollow noopener"&gt;Facebook&lt;/a&gt;&lt;/li&gt;
&lt;li&gt;&lt;a href="https://www.linkedin.com/company/teaching-python" rel="nofollow noopener"&gt;LinkedIn&lt;/a&gt;
``` Special Guest: Kelly Powers.&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>In Episode 142 of Teaching Python, hosts Sean Tibor and Kelly Schuster-Paredes are joined by Kelly Powers, a fellow middle school educator and curriculum designer, to explore the dynamic world of middle school instruction. As a passionate advocate for computational thinking, Powers shares valuable insights on introducing students to the concepts of AI, data science, and cybersecurity in a way that is both rigorous and joyful.</p>

<h2>Topics Covered</h2>

<ul>
<li><strong>Engaging Middle School Students</strong>: Strategies for capturing and maintaining student interest.</li>
<li><strong>Creativity and Collaboration</strong>: How to foster a collaborative environment that inspires creativity.</li>
<li><strong>Core Computational Concepts</strong>: Real-world applications that make these concepts accessible and interesting.</li>
<li><strong>Data Science Projects</strong>: Practical advice on integrating data science into your curriculum.</li>
<li><strong>Generative AI Ethics</strong>: Discussing the ethical use of AI in education.</li>
<li><strong>Python as a Teaching Tool</strong>: Exploring the versatility of Python for various projects.</li>
</ul>

<h2>Key Takeaways</h2>

<ul>
<li><strong><em>Integrating Computational Thinking Skills</em></strong>: Tips on how to weave these skills into everyday classroom routines.</li>
<li><strong><em>Teamwork and Communication</em></strong>: The importance of teamwork and effective communication in coding projects.</li>
<li><strong><em>Engaging Lessons with Python</em></strong>: How Python can be used to create engaging and meaningful projects for students.</li>
</ul>

<h2>About Kelly Powers</h2>

<p>Kelly Powers transitioned from the business world to education, bringing a fresh perspective on teaching computational thinking. She offers invaluable insights into making rigorous and joyful learning experiences for middle school students.</p>

<p>Whether you are an experienced teacher or new to the field, this episode is packed with actionable ideas and inspirational moments that will help you create a more engaging and effective learning environment.</p>

<p>Tune in for a lively conversation that celebrates the magic of middle school teaching and the endless possibilities of computer science education.</p>

<p><strong>Listen to the episode</strong>: <a href="https://www.teachingpython.fm/142" rel="nofollow noopener">Teaching Python Podcast</a></p>

<p><strong>Follow us on Social Media</strong>:</p>

<ul>
<li><a href="https://twitter.com/teachingpython" rel="nofollow noopener">Twitter</a></li>
<li><a href="https://www.facebook.com/teachingpython" rel="nofollow noopener">Facebook</a></li>
<li><a href="https://www.linkedin.com/company/teaching-python" rel="nofollow noopener">LinkedIn</a>
```</li>
</ul><p>Special Guest: Kelly Powers.</p><p><a rel="payment" href="https://www.patreon.com/teachingpython">Support Teaching Python</a></p><p>Links:</p><ul><li><a title="CodeHS - Teach Coding and Computer Science at Your School | CodeHS" rel="nofollow" href="https://codehs.com/">CodeHS - Teach Coding and Computer Science at Your School | CodeHS
</a> &mdash; Everything You Need, All In One Spot
CodeHS is trusted by thousands of teachers and schools all over the world.
</li><li><a title="Overview ‹ Scratch — MIT Media Lab" rel="nofollow" href="https://www.media.mit.edu/projects/scratch/overview/">Overview ‹ Scratch — MIT Media Lab
</a> &mdash; Scratch&nbsp;is the world's most popular coding community for kids. Millions of kids around the world are using Scratch to program their own interactive stories, games, and animations—and share their creations in an active online community. 
</li><li><a title="Welcome To Colab - Colab" rel="nofollow" href="https://colab.research.google.com/">Welcome To Colab - Colab
</a> &mdash; Colab is an online Jupyter notebook from Google
</li><li><a title="Computer Science Teachers Association Connect, Grow, &amp; Share With CS Teachers-" rel="nofollow" href="https://csteachers.org/">Computer Science Teachers Association Connect, Grow, &amp; Share With CS Teachers-
</a> &mdash; CSTA understands that teaching computer science is hard. That’s why we’re focused on creating a supportive environment for K–12 educators.
</li></ul>]]>
  </content:encoded>
  <itunes:summary>
    <![CDATA[<p>In Episode 142 of Teaching Python, hosts Sean Tibor and Kelly Schuster-Paredes are joined by Kelly Powers, a fellow middle school educator and curriculum designer, to explore the dynamic world of middle school instruction. As a passionate advocate for computational thinking, Powers shares valuable insights on introducing students to the concepts of AI, data science, and cybersecurity in a way that is both rigorous and joyful.</p>

<h2>Topics Covered</h2>

<ul>
<li><strong>Engaging Middle School Students</strong>: Strategies for capturing and maintaining student interest.</li>
<li><strong>Creativity and Collaboration</strong>: How to foster a collaborative environment that inspires creativity.</li>
<li><strong>Core Computational Concepts</strong>: Real-world applications that make these concepts accessible and interesting.</li>
<li><strong>Data Science Projects</strong>: Practical advice on integrating data science into your curriculum.</li>
<li><strong>Generative AI Ethics</strong>: Discussing the ethical use of AI in education.</li>
<li><strong>Python as a Teaching Tool</strong>: Exploring the versatility of Python for various projects.</li>
</ul>

<h2>Key Takeaways</h2>

<ul>
<li><strong><em>Integrating Computational Thinking Skills</em></strong>: Tips on how to weave these skills into everyday classroom routines.</li>
<li><strong><em>Teamwork and Communication</em></strong>: The importance of teamwork and effective communication in coding projects.</li>
<li><strong><em>Engaging Lessons with Python</em></strong>: How Python can be used to create engaging and meaningful projects for students.</li>
</ul>

<h2>About Kelly Powers</h2>

<p>Kelly Powers transitioned from the business world to education, bringing a fresh perspective on teaching computational thinking. She offers invaluable insights into making rigorous and joyful learning experiences for middle school students.</p>

<p>Whether you are an experienced teacher or new to the field, this episode is packed with actionable ideas and inspirational moments that will help you create a more engaging and effective learning environment.</p>

<p>Tune in for a lively conversation that celebrates the magic of middle school teaching and the endless possibilities of computer science education.</p>

<p><strong>Listen to the episode</strong>: <a href="https://www.teachingpython.fm/142" rel="nofollow noopener">Teaching Python Podcast</a></p>

<p><strong>Follow us on Social Media</strong>:</p>

<ul>
<li><a href="https://twitter.com/teachingpython" rel="nofollow noopener">Twitter</a></li>
<li><a href="https://www.facebook.com/teachingpython" rel="nofollow noopener">Facebook</a></li>
<li><a href="https://www.linkedin.com/company/teaching-python" rel="nofollow noopener">LinkedIn</a>
```</li>
</ul><p>Special Guest: Kelly Powers.</p><p><a rel="payment" href="https://www.patreon.com/teachingpython">Support Teaching Python</a></p><p>Links:</p><ul><li><a title="CodeHS - Teach Coding and Computer Science at Your School | CodeHS" rel="nofollow" href="https://codehs.com/">CodeHS - Teach Coding and Computer Science at Your School | CodeHS
</a> &mdash; Everything You Need, All In One Spot
CodeHS is trusted by thousands of teachers and schools all over the world.
</li><li><a title="Overview ‹ Scratch — MIT Media Lab" rel="nofollow" href="https://www.media.mit.edu/projects/scratch/overview/">Overview ‹ Scratch — MIT Media Lab
</a> &mdash; Scratch&nbsp;is the world's most popular coding community for kids. Millions of kids around the world are using Scratch to program their own interactive stories, games, and animations—and share their creations in an active online community. 
</li><li><a title="Welcome To Colab - Colab" rel="nofollow" href="https://colab.research.google.com/">Welcome To Colab - Colab
</a> &mdash; Colab is an online Jupyter notebook from Google
</li><li><a title="Computer Science Teachers Association Connect, Grow, &amp; Share With CS Teachers-" rel="nofollow" href="https://csteachers.org/">Computer Science Teachers Association Connect, Grow, &amp; Share With CS Teachers-
</a> &mdash; CSTA understands that teaching computer science is hard. That’s why we’re focused on creating a supportive environment for K–12 educators.
</li></ul>]]>
  </itunes:summary>
</item>
<item>
  <title>Episode 141: Unlocking Python Expertise with Trey Hunner</title>
  <link>https://www.teachingpython.fm/141</link>
  <guid isPermaLink="false">32cfa5b6-e979-4f2d-b225-4d295e308540</guid>
  <pubDate>Sat, 14 Dec 2024 07:00:00 -0500</pubDate>
  <author>Sean Tibor and Kelly Paredes</author>
  <enclosure url="https://aphid.fireside.fm/d/1437767933/c8ea6bdf-0c80-46e7-a00a-639d7dc2be91/32cfa5b6-e979-4f2d-b225-4d295e308540.mp3" length="49937257" type="audio/mpeg"/>
  <itunes:episode>141</itunes:episode>
  <itunes:title>Unlocking Python Expertise with Trey Hunner</itunes:title>
  <itunes:episodeType>full</itunes:episodeType>
  <itunes:author>Sean Tibor and Kelly Paredes</itunes:author>
  <itunes:subtitle>In this episode, hosts Kelly Schuster-Paredes and Sean Tibor are joined by Python expert Trey Hunner for an engaging and insightful conversation. Together, they explore the intricacies of teaching Python, the evolving role of AI in education, and the excitement of discovering new programming features. Join the conversation and be part of their exploration into the balance of fun and learning in the world of Python.</itunes:subtitle>
  <itunes:duration>51:32</itunes:duration>
  <itunes:explicit>no</itunes:explicit>
  <itunes:image href="https://media24.fireside.fm/file/fireside-images-2024/podcasts/images/c/c8ea6bdf-0c80-46e7-a00a-639d7dc2be91/episodes/3/32cfa5b6-e979-4f2d-b225-4d295e308540/cover.jpg?v=1"/>
  <description>&lt;p&gt;Join hosts Kelly Schuster-Paredes and Sean Tibor as they welcome esteemed Python expert Trey Hunner to the show. This episode is a delightful mix of practical insights, engaging stories, and thought-provoking discussions about Python and teaching. &lt;/p&gt;

&lt;p&gt;Trey shares his experiences with listeners, starting with his recent venture into launching a 10-week Python course called Python High Five. He talks about the excitement and challenges of teaching across different time zones with this unique setup, highlighting the importance of accountability and the fun of learning alongside his students.&lt;/p&gt;

&lt;p&gt;Throughout the episode, Sean and Kelly discuss the evolving landscape of AI and its impact on learning. Trey emphasizes the critical skill of asking the right questions, saying, "Knowing how to use that tool is a really valuable thing, but also knowing what to stick into the tool and how to evaluate the output of the tool is a really valuable thing." &lt;/p&gt;

&lt;p&gt;The conversation transitions into the heart of Python programming, where Trey, Sean, and Kelly share their favorite features and nuances of Python. They explore the value of looping helpers and marvel at the elegance and simplicity of Python's tools and functions. Sean recalls a memorable teaching moment about Python turtle graphics, reflecting on the joy and discovery that comes with coding: "It was so cool that this sixth grader showed me how to do it."&lt;/p&gt;

&lt;p&gt;This episode is not just about technical insights but also about the joy of teaching and learning. Trey, Kelly, and Sean discuss strategies for balancing the basics with advanced learning and the importance of having fun in the process. Join them for a warm, inclusive conversation that invites you to be part of their journey through the wonders of Python programming. Special Guest: Trey Hunner.&lt;/p&gt;
</description>
  <itunes:keywords>python programming, teaching python, trey hunner, ai in education, learning strategies, python features, educational technology, coding for beginners, programming tips, creative coding</itunes:keywords>
  <content:encoded>
    <![CDATA[<p>Join hosts Kelly Schuster-Paredes and Sean Tibor as they welcome esteemed Python expert Trey Hunner to the show. This episode is a delightful mix of practical insights, engaging stories, and thought-provoking discussions about Python and teaching. </p>

<p>Trey shares his experiences with listeners, starting with his recent venture into launching a 10-week Python course called Python High Five. He talks about the excitement and challenges of teaching across different time zones with this unique setup, highlighting the importance of accountability and the fun of learning alongside his students.</p>

<p>Throughout the episode, Sean and Kelly discuss the evolving landscape of AI and its impact on learning. Trey emphasizes the critical skill of asking the right questions, saying, "Knowing how to use that tool is a really valuable thing, but also knowing what to stick into the tool and how to evaluate the output of the tool is a really valuable thing." </p>

<p>The conversation transitions into the heart of Python programming, where Trey, Sean, and Kelly share their favorite features and nuances of Python. They explore the value of looping helpers and marvel at the elegance and simplicity of Python's tools and functions. Sean recalls a memorable teaching moment about Python turtle graphics, reflecting on the joy and discovery that comes with coding: "It was so cool that this sixth grader showed me how to do it."</p>

<p>This episode is not just about technical insights but also about the joy of teaching and learning. Trey, Kelly, and Sean discuss strategies for balancing the basics with advanced learning and the importance of having fun in the process. Join them for a warm, inclusive conversation that invites you to be part of their journey through the wonders of Python programming.</p><p>Special Guest: Trey Hunner.</p><p><a rel="payment" href="https://www.patreon.com/teachingpython">Support Teaching Python</a></p><p>Links:</p><ul><li><a title="Python Morsels: Write better Python code" rel="nofollow" href="https://www.pythonmorsels.com/">Python Morsels: Write better Python code
</a> &mdash; Learning efficiently requires planning a path that repeatedly answers the question what skill should I learn next and how best can I learn it? Instead of wading through blog posts and YouTube videos in search of the next thing to learn, I can guide you.

My name is Trey Hunner and I created Python Morsels to give life-long learners a low-stress way to improve their Python skills.
</li><li><a title="PEP 636 – Structural Pattern Matching: Tutorial | peps.python.org" rel="nofollow" href="https://peps.python.org/pep-0636/">PEP 636 – Structural Pattern Matching: Tutorial | peps.python.org
</a> &mdash; As an example to motivate this tutorial, you will be writing a text adventure. That is a form of interactive fiction where the user enters text commands to interact with a fictional world and receives text descriptions of what happens. Commands will be simplified forms of natural language like get sword, attack dragon, go north, enter shop or buy cheese.
</li><li><a title="Amazon.com: The Worlds I See: Curiosity, Exploration, and Discovery at the Dawn of AI eBook : Li, Fei-Fei: Kindle Store" rel="nofollow" href="https://www.amazon.com/dp/B0BPQSLVL6/ref=nosim?tag=teachingpython-20">Amazon.com: The Worlds I See: Curiosity, Exploration, and Discovery at the Dawn of AI eBook : Li, Fei-Fei: Kindle Store
</a> &mdash; The Worlds I See is a story of science in the first person, documenting one of the century’s defining moments from the inside. It provides a riveting story of a scientist at work and a thrillingly clear explanation of what artificial intelligence actually is—and how it came to be. Emotionally raw and intellectually uncompromising, this book is a testament not only to the passion required for even the most technical scholarship but also to the curiosity forever at its heart.
</li><li><a title="Blog Archive - Trey Hunner" rel="nofollow" href="https://treyhunner.com/blog/archives/">Blog Archive - Trey Hunner
</a></li></ul>]]>
  </content:encoded>
  <itunes:summary>
    <![CDATA[<p>Join hosts Kelly Schuster-Paredes and Sean Tibor as they welcome esteemed Python expert Trey Hunner to the show. This episode is a delightful mix of practical insights, engaging stories, and thought-provoking discussions about Python and teaching. </p>

<p>Trey shares his experiences with listeners, starting with his recent venture into launching a 10-week Python course called Python High Five. He talks about the excitement and challenges of teaching across different time zones with this unique setup, highlighting the importance of accountability and the fun of learning alongside his students.</p>

<p>Throughout the episode, Sean and Kelly discuss the evolving landscape of AI and its impact on learning. Trey emphasizes the critical skill of asking the right questions, saying, "Knowing how to use that tool is a really valuable thing, but also knowing what to stick into the tool and how to evaluate the output of the tool is a really valuable thing." </p>

<p>The conversation transitions into the heart of Python programming, where Trey, Sean, and Kelly share their favorite features and nuances of Python. They explore the value of looping helpers and marvel at the elegance and simplicity of Python's tools and functions. Sean recalls a memorable teaching moment about Python turtle graphics, reflecting on the joy and discovery that comes with coding: "It was so cool that this sixth grader showed me how to do it."</p>

<p>This episode is not just about technical insights but also about the joy of teaching and learning. Trey, Kelly, and Sean discuss strategies for balancing the basics with advanced learning and the importance of having fun in the process. Join them for a warm, inclusive conversation that invites you to be part of their journey through the wonders of Python programming.</p><p>Special Guest: Trey Hunner.</p><p><a rel="payment" href="https://www.patreon.com/teachingpython">Support Teaching Python</a></p><p>Links:</p><ul><li><a title="Python Morsels: Write better Python code" rel="nofollow" href="https://www.pythonmorsels.com/">Python Morsels: Write better Python code
</a> &mdash; Learning efficiently requires planning a path that repeatedly answers the question what skill should I learn next and how best can I learn it? Instead of wading through blog posts and YouTube videos in search of the next thing to learn, I can guide you.

My name is Trey Hunner and I created Python Morsels to give life-long learners a low-stress way to improve their Python skills.
</li><li><a title="PEP 636 – Structural Pattern Matching: Tutorial | peps.python.org" rel="nofollow" href="https://peps.python.org/pep-0636/">PEP 636 – Structural Pattern Matching: Tutorial | peps.python.org
</a> &mdash; As an example to motivate this tutorial, you will be writing a text adventure. That is a form of interactive fiction where the user enters text commands to interact with a fictional world and receives text descriptions of what happens. Commands will be simplified forms of natural language like get sword, attack dragon, go north, enter shop or buy cheese.
</li><li><a title="Amazon.com: The Worlds I See: Curiosity, Exploration, and Discovery at the Dawn of AI eBook : Li, Fei-Fei: Kindle Store" rel="nofollow" href="https://www.amazon.com/dp/B0BPQSLVL6/ref=nosim?tag=teachingpython-20">Amazon.com: The Worlds I See: Curiosity, Exploration, and Discovery at the Dawn of AI eBook : Li, Fei-Fei: Kindle Store
</a> &mdash; The Worlds I See is a story of science in the first person, documenting one of the century’s defining moments from the inside. It provides a riveting story of a scientist at work and a thrillingly clear explanation of what artificial intelligence actually is—and how it came to be. Emotionally raw and intellectually uncompromising, this book is a testament not only to the passion required for even the most technical scholarship but also to the curiosity forever at its heart.
</li><li><a title="Blog Archive - Trey Hunner" rel="nofollow" href="https://treyhunner.com/blog/archives/">Blog Archive - Trey Hunner
</a></li></ul>]]>
  </itunes:summary>
</item>
  </channel>
</rss>
