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Development

Episode 33 — “Up, Down, and All Around” — Doland White, Part 2

In today’s episode, we’re wrapping up the conversation (for now, at least) with Doland White on leadership. I’m not quite sure how it happened, but there’s a lot of good stuff packed into this one episode. I hope you take full advantage of it!

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Episode 31 — “How To Fail At Leadership While Actually Trying”

In this episode, we’re starting a conversation about a new, non-traditional approach to leadership and leadership development. Before diving into the details, we address one of the key elements that can sabotage both new and seasoned leaders. Listen to the episode now [Open the player page] Resources

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Episode 30 — “Career Management in Uncertain Times” — Shane Carlson, Part 2

In this episode, I finish up my conversation with Shane Carlson on career management. There’s some really great ideas in here and a couple of stories that help make the point. It’s slightly longer than usual, so be prepared. Please come back to provide questions, comments, and feedback. Listen to the episode now [Open the

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Episode 29 — “Career Management in Uncertain Times” — Shane Carlson

In this episode, I talk with my long-time friend Shane Carlson about “career management” and whether it’s “still a thing.” With the number of layoffs in the tech sector, I think it’s a very relevant topic and a question worth entertaining. If you’ve spent even a moment considering your career and your future, I think

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Thank you!

Today, I’d like to extend my heartfelt thanks to those who’ve avidly followed my podcast, “Esoteric Curiosities.” This podcast is not just a “labor of love” for me; it’s a vital part of my personal mission and self-expression. I am driven to share as much of the knowledge and experiences I’ve gathered over the course

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Episode 17 – “Data, Data, Everywhere!” – Dr. Mauricio Corona, Part 3I

In this episode, kengon finishes his conversation with Mauricio, talking about the massive amounts of data available today and how people can get started down the path of being a member of a multidisciplinary data science team

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