39 min
How to Future Proof Your Career in Data Science with Chris Bishop HumAIn Podcast - Artificial Intelligence, Data Science, Developer Tools, and Technical Education
-
- Technology
[Audio]
Podcast: Play in new window | Download
Subscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSS
Chris Bishop has a degree in German Literature from Bennington College. He started music after getting out of school.He ended up in the jingle business, writing music for television. Then he became intrigued by the web and taught himself to be a web producer and worked at a couple of seminal interactive agencies in New York. He was hired by IBM into their fledgling corporate internet programs division.
He is a TEDx speaker, ex-IBMer, former NYC studio cat, future workplace consultant, and a firm believer in the power of focusing on the fringe. Based on his own nonlinear, multimodal career path he’s developed a workshop called “How to succeed at jobs that don’t exist yet” designed to excite and empower today's learners as they navigate the global borderless workplace.His session provides insight into how to deliver business results and pursue successful careers leveraging emerging technologies including quantum information science, AI, data science, fintech, cryptoassets, blockchain, augmented/virtual reality, genomic editing, and robotics.
Episode Links:
Chris Bishop’s LinkedIn: https://www.linkedin.com/in/christopherbishop123/
Chris Bishop’s Twitter: @chrisbishop
Chris Bishop’s Website: https://improvisingcareers.com/
Podcast Details:
Podcast website: https://www.humainpodcast.com
Apple Podcasts: https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009
Spotify: https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpS
RSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9
YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag
YouTube Clips: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videos
Support and Social Media:
– Check out the sponsors above, it’s the best way to support this podcast
– Support on Patreon: https://www.patreon.com/humain/creators
– Twitter: https://twitter.com/dyakobovitch
– Instagram: https://www.instagram.com/humainpodcast/
– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/
– Facebook: https://www.facebook.com/HumainPodcast/
– HumAIn Website Articles: https://www.humainpodcast.com/blog/
Outline:
Here’s the timestamps for the episode:
(00:00) – Introduction
(04:38) – The U.S Bureau of Labor and Statistics says today's learners will have 8-10 jobs by the time they're 38. They're going to use technology that doesn't exist today. I connected with a gentleman from LinkedIn Learning and he said, I think your content would be valuable to the LinkedIn Learning audience and here we are.
(06:18) – People can work from home or from wherever on the train or in a Starbucks and be more productive, because they're more in control of their time. Data science is going to have lots of opportunities to take these learnings, as you said about education. The opportunity again, for data science to rethink how information is shared and distributed represents a huge opportunity.
(08:36) – The idea is that humans have been creating devices to make work simpler and faster and easier for literally thousands of years. There's lots of history and precedents for the kinds of tools that led to humans manipulating data, that is what we do today with algorithms and using artificial intelligence and machine learning. So it is part of a long arc that goes back thousands of years and is going to continue for thousands of years.
(11:38) – An interesting example to share is the New York Stock Exchange. That space is basically a catering hall now, because there are algorithms that are doing most of the trading. There are certainly people in there doing work, but back to your comment about math, algorithms can make assessments and recommendations, buy and sell way faster than a human can. So that's the model, it is like, let's use tool
[Audio]
Podcast: Play in new window | Download
Subscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSS
Chris Bishop has a degree in German Literature from Bennington College. He started music after getting out of school.He ended up in the jingle business, writing music for television. Then he became intrigued by the web and taught himself to be a web producer and worked at a couple of seminal interactive agencies in New York. He was hired by IBM into their fledgling corporate internet programs division.
He is a TEDx speaker, ex-IBMer, former NYC studio cat, future workplace consultant, and a firm believer in the power of focusing on the fringe. Based on his own nonlinear, multimodal career path he’s developed a workshop called “How to succeed at jobs that don’t exist yet” designed to excite and empower today's learners as they navigate the global borderless workplace.His session provides insight into how to deliver business results and pursue successful careers leveraging emerging technologies including quantum information science, AI, data science, fintech, cryptoassets, blockchain, augmented/virtual reality, genomic editing, and robotics.
Episode Links:
Chris Bishop’s LinkedIn: https://www.linkedin.com/in/christopherbishop123/
Chris Bishop’s Twitter: @chrisbishop
Chris Bishop’s Website: https://improvisingcareers.com/
Podcast Details:
Podcast website: https://www.humainpodcast.com
Apple Podcasts: https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009
Spotify: https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpS
RSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9
YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag
YouTube Clips: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videos
Support and Social Media:
– Check out the sponsors above, it’s the best way to support this podcast
– Support on Patreon: https://www.patreon.com/humain/creators
– Twitter: https://twitter.com/dyakobovitch
– Instagram: https://www.instagram.com/humainpodcast/
– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/
– Facebook: https://www.facebook.com/HumainPodcast/
– HumAIn Website Articles: https://www.humainpodcast.com/blog/
Outline:
Here’s the timestamps for the episode:
(00:00) – Introduction
(04:38) – The U.S Bureau of Labor and Statistics says today's learners will have 8-10 jobs by the time they're 38. They're going to use technology that doesn't exist today. I connected with a gentleman from LinkedIn Learning and he said, I think your content would be valuable to the LinkedIn Learning audience and here we are.
(06:18) – People can work from home or from wherever on the train or in a Starbucks and be more productive, because they're more in control of their time. Data science is going to have lots of opportunities to take these learnings, as you said about education. The opportunity again, for data science to rethink how information is shared and distributed represents a huge opportunity.
(08:36) – The idea is that humans have been creating devices to make work simpler and faster and easier for literally thousands of years. There's lots of history and precedents for the kinds of tools that led to humans manipulating data, that is what we do today with algorithms and using artificial intelligence and machine learning. So it is part of a long arc that goes back thousands of years and is going to continue for thousands of years.
(11:38) – An interesting example to share is the New York Stock Exchange. That space is basically a catering hall now, because there are algorithms that are doing most of the trading. There are certainly people in there doing work, but back to your comment about math, algorithms can make assessments and recommendations, buy and sell way faster than a human can. So that's the model, it is like, let's use tool
39 min