app03 Fri, 02 Oct 2026 10:44:53 +0000 Fireside (https://fireside.fm) Teaching Python - Episodes Tagged with “Learning With Ai” https://www.teachingpython.fm/tags/learning%20with%20ai Fri, 02 Oct 2026 00:00:00 -0400 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. en-us episodic We're two computer science educators learning and teaching Python Sean Tibor and Kelly Paredes 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. no 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 Sean Tibor and Kelly Paredes sean.tibor@gmail.com Episode 163: How Do You Find Time to Keep Learning? https://www.teachingpython.fm/163 015a6951-f639-4009-a58b-88c95d0175ad Fri, 02 Oct 2026 00:00:00 -0400 Sean Tibor and Kelly Paredes 163 How Do You Find Time to Keep Learning? full Sean Tibor and Kelly Paredes Teaching Python started as a podcast about teaching programming in the classroom. But both the hosts and the world around Python have changed. In this episode, Kelly and Julian reflect on what *Teaching Python* means in 2026, as Python increasingly sits inside a much larger computing landscape that includes AI, data, cybersecurity, cloud, software engineering, systems thinking, and automation. They explore why Python still matters when AI can generate code, how the skills around programming are changing, and why reading, debugging, evaluating, testing, and modifying code may matter more than simply producing it. The conversation also looks at the changing role of the teacher, coach, and learner when AI can become another source of guidance. Python is still here. But teaching Python now is increasingly about helping people understand, build, question, and make decisions with technology. 52:40 no <p>How do you keep learning when there never seems to be enough time?</p> <p>The answer may be less about finding more time and more about building learning into the way you already work, solve problems, use AI, and connect with other people.</p> <p>In Episode 163 of the Teaching Python Podcast, Sean Tibor, Kelly Schuster-Paredes, and Julian Sequeira discuss how they keep learning in a technology landscape shaped by rapid changes in AI, software development, and computing.</p> <p>They compare practical approaches to continuous learning, including building projects, using commutes and downtime, scheduling dedicated learning time, asking ChatGPT and Claude questions as they come up, watching webinars, reading, experimenting with new tools, and learning from professional networks.</p> <p>The conversation also explores what happens when you need to learn something you are not naturally interested in. They discuss adult learning, desirable difficulty, just-in-time learning, recursive learning, and why struggling with unfamiliar ideas can still be valuable even when AI can explain concepts instantly.</p> <p>Along the way, they talk about vibe coding, AI as a learning partner, professional development, technical communities, balancing creation and consumption, and setting boundaries so that continuous learning does not become constant burnout.</p> <p>If you are trying to keep up with AI, learn new technology, or continue developing technical skills without turning every spare moment into work, this episode offers a practical look at how learning can become part of everyday life. </p> teaching python, continuous learning, recursive learning, lifelong learning, adult learning, learning how to learn, learning in technology, learning in tech, AI learning, AI for learning, learning with AI, keeping up with AI, keeping up with technology, learning new technology, ChatGPT for learning, Claude AI, AI learning partner, vibe coding, just-in-time learning, professional development, professional learning, technical skills, software development, coding, computer science, educational technology, edtech, digital literacy, AI literacy, knowledge work, productivity, time management, priority management, technical communities, professional networks, learning by building, project-based learning, desirable difficulty, burnout, work-life balance, technology careers, lifelong professional learning How do you keep learning when there never seems to be enough time?

The answer may be less about finding more time and more about building learning into the way you already work, solve problems, use AI, and connect with other people.

In Episode 163 of the Teaching Python Podcast, Sean Tibor, Kelly Schuster-Paredes, and Julian Sequeira discuss how they keep learning in a technology landscape shaped by rapid changes in AI, software development, and computing.

They compare practical approaches to continuous learning, including building projects, using commutes and downtime, scheduling dedicated learning time, asking ChatGPT and Claude questions as they come up, watching webinars, reading, experimenting with new tools, and learning from professional networks.

The conversation also explores what happens when you need to learn something you are not naturally interested in. They discuss adult learning, desirable difficulty, just-in-time learning, recursive learning, and why struggling with unfamiliar ideas can still be valuable even when AI can explain concepts instantly.

Along the way, they talk about vibe coding, AI as a learning partner, professional development, technical communities, balancing creation and consumption, and setting boundaries so that continuous learning does not become constant burnout.

If you are trying to keep up with AI, learn new technology, or continue developing technical skills without turning every spare moment into work, this episode offers a practical look at how learning can become part of everyday life.

Support Teaching Python

]]> How do you keep learning when there never seems to be enough time?

The answer may be less about finding more time and more about building learning into the way you already work, solve problems, use AI, and connect with other people.

In Episode 163 of the Teaching Python Podcast, Sean Tibor, Kelly Schuster-Paredes, and Julian Sequeira discuss how they keep learning in a technology landscape shaped by rapid changes in AI, software development, and computing.

They compare practical approaches to continuous learning, including building projects, using commutes and downtime, scheduling dedicated learning time, asking ChatGPT and Claude questions as they come up, watching webinars, reading, experimenting with new tools, and learning from professional networks.

The conversation also explores what happens when you need to learn something you are not naturally interested in. They discuss adult learning, desirable difficulty, just-in-time learning, recursive learning, and why struggling with unfamiliar ideas can still be valuable even when AI can explain concepts instantly.

Along the way, they talk about vibe coding, AI as a learning partner, professional development, technical communities, balancing creation and consumption, and setting boundaries so that continuous learning does not become constant burnout.

If you are trying to keep up with AI, learn new technology, or continue developing technical skills without turning every spare moment into work, this episode offers a practical look at how learning can become part of everyday life.

Support Teaching Python

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