Conversations with women in STEAM (science, technology, engineering, mathematics, and medicine) about their journeys, work, passions, and what they learned along the way. We’re a diverse group of people with unique personal and professional journeys, and I want you to meet some of us.This podcast uses the following third-party services for analysis: Podscribe - https://podscribe.com/privacyChartable - https://chartable.com/privacyOP3 - https://op3.dev/privacyPodsights - https://podsights.com/privacy
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episode 63: The interconnectedness of seemingly disparate things with Laura Langdon
It's not about the destination, it's about the journey. But for today's guest, it's about both. Laura Langdon is a developer advocate who has the pleasure of combining her explorations and experience in theatre, computer science, mathematics, education, and data science into a role that rolls all of that into one perfect package. Join us as we speak of about Laura's experience in education, and the beauty of the interconnectedness of seemingly disparate things.
About Laura Langdon
Laura Langdon is a Developer Advocate at Suborbital Software Systems, where she manages documentation and participates in outreach activities, especially around the intersections data science, Python, and extensibility. Previously a math lecturer at CSU East Bay, Laura is devoted to issues in pedagogy, neurodivergence, and social responsibility in tech. In her free time, she enjoys recreational research, optimising all the things, and not trying to think of a third thing with which to end this sentence.
Show Notes (link)
[00:00:53] Laura opting out of high school and going through community college instead.
[00:04:33] Why college was a better fit for Laura.
[00:07:04] The path of human experience.
[00:11:48] Coming to settle her explorations with mathematics.
[00:14:00] Laura's epiphany with mathematics.
[00:17:35] Practical considerations when it comes to choosing your path.
[00:22:59] The beauty of pure mathematics that we miss out on at school.
[00:23:31] Sometimes material is hard. But sometimes it's hard because people have different modes of learning.
[00:25:25] Resources can be crutches. What do you want to get out of this?
[00:26:31] Speak to course advisors and coordinators. There may be options you weren't aware of.
[00:29:25] Why homeschooling.
[00:32:20] The Montessori method
[00:36:12] AI, Reinforcement Learning, and DeepMind.
[00:38:20] Finding her way to technical writing.
[00:43:48] Ethics, algorithms, and society.
[00:47:39] A day in the life of developer relations.
[00:49:01] Bringing all those accumulated skills together.
[00:51:15] What advice would you give someone who wants to do what you do? And what advice should they ignore?
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Hosted and produced by Michele Ong.
Music is "Gypsy Jazz in Paris 1935" by Brett Van Donsel.
This podcast uses the following third-party services for analysis:
Chartable - https://chartable.com/privacy
OP3 - https://op3.dev/privacy
Podsights - https://podsights.com/privacy