app01 Sat, 25 Jul 2026 23:55:16 +0000 Fireside (https://fireside.fm) Teaching Python - Episodes Tagged with “Cybersecurity” https://www.teachingpython.fm/tags/cybersecurity Mon, 22 Jun 2026 00:00:00 -0400 Welcome to "Teaching Python Podcast,” the go-to podcast for anyone interested in the intersection of education and coding. Hosted by Kelly Paredes and Sean Tibor, this podcast dives into the thrills and challenges of teaching computer science through the engaging and versatile Python programming language. About the Hosts: Kelly Paredes brings a wealth of global experience in curriculum design and currently inspires sixth and eighth graders at Pine Crest School in Fort Lauderdale, Florida. Celebrating her seventh year of integrating Python into her teaching, Kelly has a knack for making complex concepts accessible and exciting. Sean Tibor, a Cloud, Infrastructure, and Networks leader at Pfizer, draws from a rich background that spans marketing, database design, and digital agency leadership. Having taught Python to seventh and eighth graders at Pine Crest School, Sean now extends his expertise by supporting interns and tutoring students in Python. Explore with Us: Engaging Lessons: Discover how we make Python programming both fun and accessible for young learners, equipping them with the skills to tackle real-world problems. Classroom Insights: Experience our journey through both triumphs and trials in the classroom, and learn what it takes to foster a vibrant learning environment. Expert Interviews: Gain valuable perspectives from interviews with fellow educators and industry experts, who share their top strategies and success stories in coding education. en-us episodic We're two computer science educators learning and teaching Python Sean Tibor and Kelly Paredes Welcome to "Teaching Python Podcast,” the go-to podcast for anyone interested in the intersection of education and coding. Hosted by Kelly Paredes and Sean Tibor, this podcast dives into the thrills and challenges of teaching computer science through the engaging and versatile Python programming language. About the Hosts: Kelly Paredes brings a wealth of global experience in curriculum design and currently inspires sixth and eighth graders at Pine Crest School in Fort Lauderdale, Florida. Celebrating her seventh year of integrating Python into her teaching, Kelly has a knack for making complex concepts accessible and exciting. Sean Tibor, a Cloud, Infrastructure, and Networks leader at Pfizer, draws from a rich background that spans marketing, database design, and digital agency leadership. Having taught Python to seventh and eighth graders at Pine Crest School, Sean now extends his expertise by supporting interns and tutoring students in Python. Explore with Us: Engaging Lessons: Discover how we make Python programming both fun and accessible for young learners, equipping them with the skills to tackle real-world problems. Classroom Insights: Experience our journey through both triumphs and trials in the classroom, and learn what it takes to foster a vibrant learning environment. Expert Interviews: Gain valuable perspectives from interviews with fellow educators and industry experts, who share their top strategies and success stories in coding education. no Digital Literacy, Coding for Kids ,Tech Integration in Education, 21st Century Skills, Blended Learning, Remote Learning, Adaptive Learning Technologies, Student Engagement Strategies, Flipped Classroom, Inquiry-Based Learning,education, python, computer science, teaching, pedagogy, STEM education, programming languages, educational technology, curriculum development, instructional design, e-learning, teacher training, data science, machine learning, higher education, tech education, innovative teaching, lesson planning, edtech tools, professional development Sean Tibor and Kelly Paredes sean.tibor@gmail.com Episode 159: Big Lessons from Small Models with Gwyneth Peña‑Siguenza https://www.teachingpython.fm/159 3ad72582-1a89-4d55-8e24-a6799da8a5a9 Mon, 22 Jun 2026 00:00:00 -0400 Sean Tibor and Kelly Paredes 159 Big Lessons from Small Models with Gwyneth Peña‑Siguenza full Sean Tibor and Kelly Paredes 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. 56:15 no <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> 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 What can small language models teach us that the largest AI models cannot?

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.

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.

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.

Show Notes

Wins of the Week

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

Small Language Models

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

Learning Through Constraints

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

Self-Taught Learning

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

Python Journey

  • Transitioning from cloud engineering to Python advocacy
  • Learning Python beyond scripting
  • Discovering what "Pythonic" really means
  • Wrestling with list comprehensions and other advanced syntax
  • Favorite learning resources:
    • Fluent Python
    • Effective Python

Learn to Cloud

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

Cloud, AI, and Security

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

Teaching in the AI Era

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

Final Thoughts

  • AI dependency versus capability
  • Judgment as the skill that matters most
  • Human connection in an AI-driven world
  • Would we actually turn AI off?
  • Finding balance between technological progress and intentional learning

Support Teaching Python

]]> What can small language models teach us that the largest AI models cannot?

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.

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.

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.

Show Notes

Wins of the Week

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

Small Language Models

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

Learning Through Constraints

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

Self-Taught Learning

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

Python Journey

  • Transitioning from cloud engineering to Python advocacy
  • Learning Python beyond scripting
  • Discovering what "Pythonic" really means
  • Wrestling with list comprehensions and other advanced syntax
  • Favorite learning resources:
    • Fluent Python
    • Effective Python

Learn to Cloud

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

Cloud, AI, and Security

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

Teaching in the AI Era

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

Final Thoughts

  • AI dependency versus capability
  • Judgment as the skill that matters most
  • Human connection in an AI-driven world
  • Would we actually turn AI off?
  • Finding balance between technological progress and intentional learning

Support Teaching Python

]]> Episode 142: Middle School Magic: Integrating AI, Data Science, and Computational Thinking with Kelly Powers https://www.teachingpython.fm/142 28ac0fd5-3b5f-46c2-9dae-56480c23a1d2 Sun, 22 Dec 2024 14:00:00 -0500 Sean Tibor and Kelly Paredes 142 Middle School Magic: Integrating AI, Data Science, and Computational Thinking with Kelly Powers full Sean Tibor and Kelly Paredes 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! 1:00:01 no <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> ``` Special Guest: Kelly Powers.</li> </ul> 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 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.

Topics Covered

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

Key Takeaways

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

About Kelly Powers

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.

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.

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

Listen to the episode: Teaching Python Podcast

Follow us on Social Media:

Special Guest: Kelly Powers.

Support Teaching Python

Links:

]]> 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.

Topics Covered

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

Key Takeaways

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

About Kelly Powers

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.

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.

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

Listen to the episode: Teaching Python Podcast

Follow us on Social Media:

Special Guest: Kelly Powers.

Support Teaching Python

Links:

]]> Episode 87: Cybersecurity Careers https://www.teachingpython.fm/87 57ffec6c-74d8-49bc-bcb4-bcee74f3cd51 Wed, 23 Mar 2022 00:00:00 -0400 Sean Tibor and Kelly Paredes 87 Cybersecurity Careers full Sean Tibor and Kelly Paredes 42:37 no <p>In the 2007 film, Shift Happens, Carl Fisch stated that “The top 10 in-demand jobs in 2010 did not exist in 2004. We are currently preparing students for jobs that don’t exist yet, using technologies that haven’t been invented, in order to solve problems we don’t even know are problems yet.” </p> <p>While the data that was used during the video cannot be completely verifiable, it is safe to say that the jobs of today have evolved quite a bit since 2004. In addition, a lot of these fields are global, rely heavily on technology and the use of code skills like Python programming. In this podcast series, we will speak to professionals in the field that have jobs in industries including Fintech 3.0, Cybertechnology, and Data Science.</p> <p>We welcome Michele Darayanani, Nevena Lazarevic and Joe Farajallah to discuss the basics of Cybersecurity, what it is, what all does it involve, and how Python can be used to secure platforms from cyber attacks. </p> <p>Michele leads the Cyber offerings for Pharmaceutical, Life Sciences, and Medical Device Manufacturing clients. An avid advocate for usable security that drives business value through Cyber; he supports clients as a sounding board for the CISO, CISO coaching, Secure Cloud Transformations, Cyber Due Diligence, and Security Architecture.</p> <p>Nevena is a passionate and proactive Cyber Security consultant with a Software Engineering background. Her focus within this area has been Cyber Defense, Security Transformation and Information Security. </p> <p>Joe is a Cyber Security consultant focusing on ethical hacking and red team testing. He has a background in electrical engineering and networks.<br> Special Guests: Joe Farajallah, Michele Daryanani, and Nevena Lazarevic.</p> python,cybersecurity,careers In the 2007 film, Shift Happens, Carl Fisch stated that “The top 10 in-demand jobs in 2010 did not exist in 2004. We are currently preparing students for jobs that don’t exist yet, using technologies that haven’t been invented, in order to solve problems we don’t even know are problems yet.”

While the data that was used during the video cannot be completely verifiable, it is safe to say that the jobs of today have evolved quite a bit since 2004. In addition, a lot of these fields are global, rely heavily on technology and the use of code skills like Python programming. In this podcast series, we will speak to professionals in the field that have jobs in industries including Fintech 3.0, Cybertechnology, and Data Science.

We welcome Michele Darayanani, Nevena Lazarevic and Joe Farajallah to discuss the basics of Cybersecurity, what it is, what all does it involve, and how Python can be used to secure platforms from cyber attacks.

Michele leads the Cyber offerings for Pharmaceutical, Life Sciences, and Medical Device Manufacturing clients. An avid advocate for usable security that drives business value through Cyber; he supports clients as a sounding board for the CISO, CISO coaching, Secure Cloud Transformations, Cyber Due Diligence, and Security Architecture.

Nevena is a passionate and proactive Cyber Security consultant with a Software Engineering background. Her focus within this area has been Cyber Defense, Security Transformation and Information Security.

Joe is a Cyber Security consultant focusing on ethical hacking and red team testing. He has a background in electrical engineering and networks.

Special Guests: Joe Farajallah, Michele Daryanani, and Nevena Lazarevic.

Support Teaching Python

Links:

  • Jobs - KPMG Switzerland — KPMG offers you excellent career prospects and a great corporate culture. We employ over 2100 talented people from 55 countries. Find out who we are, what we do, what we find important and what day-to-day work at KPMG is really like. We are seeking people who have a “dare to do” attitude, for our company prospers with the help of courageous people. Choose your level of experience and take a look at our job vacancies.
  • python-ldap · PyPI — python-ldap provides an object-oriented API to access LDAP directory servers from Python programs. Mainly it wraps the OpenLDAP 2.x libs for that purpose. Additionally the package contains modules for other LDAP-related stuff (e.g. processing LDIF, LDAPURLs, LDAPv3 schema, LDAPv3 extended operations and controls, etc.).
]]> In the 2007 film, Shift Happens, Carl Fisch stated that “The top 10 in-demand jobs in 2010 did not exist in 2004. We are currently preparing students for jobs that don’t exist yet, using technologies that haven’t been invented, in order to solve problems we don’t even know are problems yet.”

While the data that was used during the video cannot be completely verifiable, it is safe to say that the jobs of today have evolved quite a bit since 2004. In addition, a lot of these fields are global, rely heavily on technology and the use of code skills like Python programming. In this podcast series, we will speak to professionals in the field that have jobs in industries including Fintech 3.0, Cybertechnology, and Data Science.

We welcome Michele Darayanani, Nevena Lazarevic and Joe Farajallah to discuss the basics of Cybersecurity, what it is, what all does it involve, and how Python can be used to secure platforms from cyber attacks.

Michele leads the Cyber offerings for Pharmaceutical, Life Sciences, and Medical Device Manufacturing clients. An avid advocate for usable security that drives business value through Cyber; he supports clients as a sounding board for the CISO, CISO coaching, Secure Cloud Transformations, Cyber Due Diligence, and Security Architecture.

Nevena is a passionate and proactive Cyber Security consultant with a Software Engineering background. Her focus within this area has been Cyber Defense, Security Transformation and Information Security.

Joe is a Cyber Security consultant focusing on ethical hacking and red team testing. He has a background in electrical engineering and networks.

Special Guests: Joe Farajallah, Michele Daryanani, and Nevena Lazarevic.

Support Teaching Python

Links:

  • Jobs - KPMG Switzerland — KPMG offers you excellent career prospects and a great corporate culture. We employ over 2100 talented people from 55 countries. Find out who we are, what we do, what we find important and what day-to-day work at KPMG is really like. We are seeking people who have a “dare to do” attitude, for our company prospers with the help of courageous people. Choose your level of experience and take a look at our job vacancies.
  • python-ldap · PyPI — python-ldap provides an object-oriented API to access LDAP directory servers from Python programs. Mainly it wraps the OpenLDAP 2.x libs for that purpose. Additionally the package contains modules for other LDAP-related stuff (e.g. processing LDIF, LDAPURLs, LDAPv3 schema, LDAPv3 extended operations and controls, etc.).
]]>