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S03E08 - The market view of data education - with Richie Cotton

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Treść dostarczona przez Half Stack Data Science. Cała zawartość podcastów, w tym odcinki, grafika i opisy podcastów, jest przesyłana i udostępniana bezpośrednio przez Half Stack Data Science lub jego partnera na platformie podcastów. Jeśli uważasz, że ktoś wykorzystuje Twoje dzieło chronione prawem autorskim bez Twojej zgody, możesz postępować zgodnie z procedurą opisaną tutaj https://pl.player.fm/legal.

A reminder that David's book, Solve Any Data Analysis Problem, is out later this year and you can already buy it and read it in its draft form as part of Manning's Early Access Program. If you want to practise your data skills on real world problems and learn a reusable framework to use on any project in the future, this book is for you.

Find out more here: https://www.manning.com/books/solve-any-data-analysis-problem

Now onto today's episode. We're continuing our series of conversations about data education and in this episode we spoke to Richie Cotton.

Richie is a data evangelist at DataCamp. He started his career as a data scientist, working in industries from chemical health and safety to debt collection to proteomics. After joining DataCamp in 2016, he switched to teaching data and AI skills. He has created ten courses on data science that have been taken by over 700k learners, and worked with instructors to create over 50 courses that have been taken by millions of learners. Richie has also written two books and R programming, Learning R and Testing R Code.

In his current role, Richie hosts the DataFramed podcast and runs the DataCamp webinar program, as well as creating tutorials and cheat sheets for data and AI skills.

We spoke to Richie about how DataCamp's offering and focus has changed over time to meet market demands, with some inevitable comments about Python vs R, what the impact of generative AI has been on data education, and what the future holds.

You can find Richie and his work on various parts of the internet:

  continue reading

29 odcinków

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iconUdostępnij
 
Manage episode 405848801 series 2423821
Treść dostarczona przez Half Stack Data Science. Cała zawartość podcastów, w tym odcinki, grafika i opisy podcastów, jest przesyłana i udostępniana bezpośrednio przez Half Stack Data Science lub jego partnera na platformie podcastów. Jeśli uważasz, że ktoś wykorzystuje Twoje dzieło chronione prawem autorskim bez Twojej zgody, możesz postępować zgodnie z procedurą opisaną tutaj https://pl.player.fm/legal.

A reminder that David's book, Solve Any Data Analysis Problem, is out later this year and you can already buy it and read it in its draft form as part of Manning's Early Access Program. If you want to practise your data skills on real world problems and learn a reusable framework to use on any project in the future, this book is for you.

Find out more here: https://www.manning.com/books/solve-any-data-analysis-problem

Now onto today's episode. We're continuing our series of conversations about data education and in this episode we spoke to Richie Cotton.

Richie is a data evangelist at DataCamp. He started his career as a data scientist, working in industries from chemical health and safety to debt collection to proteomics. After joining DataCamp in 2016, he switched to teaching data and AI skills. He has created ten courses on data science that have been taken by over 700k learners, and worked with instructors to create over 50 courses that have been taken by millions of learners. Richie has also written two books and R programming, Learning R and Testing R Code.

In his current role, Richie hosts the DataFramed podcast and runs the DataCamp webinar program, as well as creating tutorials and cheat sheets for data and AI skills.

We spoke to Richie about how DataCamp's offering and focus has changed over time to meet market demands, with some inevitable comments about Python vs R, what the impact of generative AI has been on data education, and what the future holds.

You can find Richie and his work on various parts of the internet:

  continue reading

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