Half Stack Data Science

Half Stack Data Science
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Half Stack Data Science

"Half Stack Data Science" is a podcast by David Asboth and Shaun McGirr about the realities of Data Science in the enterprise business world.

  1. 22 МАЯ

    S03E10 - Data science needs you! - with Andrea Jones-Rooy

    If you're an aspiring analyst and want to test your existing data skills on real-world problems while learning both new skills and a framework you can apply to any problem, David's book Solve Any Data Analysis Problem is available on the Manning website through the Early Access Program and it's out in print later this year. Find it at https://www.manning.com/books/solve-any-data-analysis-problem In this episode, we welcome back a former guest, Andrea Jones-Rooy, Ph.D. Andrea is the founder of Data Thinking, an organization dedicated to promoting worldwide data literacy and public involvement in data science. Previously, she was the Director of Undergraduate Studies and Visiting Associate Professor at the NYU Center for Data Science, where she developed and taught their flagship course, Data Science for Everyone, as well as advanced courses on Natural Language Processing. Dr. Jones-Rooy believes everyone has a role to play in data science, and you (yes, you!) can get involved at DataScienceNeedsYou.com! We spoke to Andrea about how to teach people the scientific method and to deal with uncertainty, the impact of generative AI on teaching these topics, whether these skills should be called "data thinking" instead of "data science", and how you even convince people these are the skills worth learning. Find Andrea at https://datascienceneedsyou.com or on social media platforms as @jonesrooy

    1 ч.

  2. 21 АПР.

    S03E09 - Statistical rethinking - with Richard McElreath

    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. In this episode, we spoke to Richard McElreath. Richard is an anthropologist focused on the role of culture in human evolution and adaptation. He is currently the Director of the Max Planck Institute for Evolutionary Anthropology in Leipzig, Germany. A major focus of the department is integrating theory with data analysis and study design, and Richard spends much of his time supporting his colleagues in that way. He is the author of Statistical Rethinking, a popular Bayesian statistics textbook and video course. We spoke to Richard about the state of scientific research, parallels between the problems in scientific research and doing data analysis in the business world, and to quote Richard, how, if we are very careful and try very hard, we might not completely mislead ourselves. Richard's departmental page: https://www.eva.mpg.de/ecology/staff/richard-mcelreath Richard's blog: https://elevanth.org/blog Richard on Twitter: https://twitter.com/rlmcelreath

    1 ч. 5 мин.

  3. 11 МАР.

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

    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: Connect with Richie on LinkedIn: https://www.linkedin.com/in/richierocks Listen to the DataFramed podcast: https://www.datacamp.com/podcast Attend DataCamp webinars: https://www.datacamp.com/webinars

    47 мин.

  4. 19.12.2023

    S03E07 - The power of data storytelling - with Kat Greenbrook

    A reminder that David's book Solve Any Data Analysis Problem is available in Manning's Early Access Program! You can read more about it here: ⁠https://www.manning.com/books/solve-any-data-analysis-problem⁠ (if it's not on offer when you're there, you can get 35% off with the code au35asb). ----------------------------------------------- In today's episode, we talked to Kat Greenbrook. Kat is a Data Storyteller from Aotearoa, New Zealand. She is a consultant, workshop facilitator, industry speaker, and founder of the data storytelling company Rogue Penguin. With a unique blend of science, business, and design, she empowers data professionals to communicate data effectively through storytelling. Her book, The Data Storyteller's Handbook is out now! You can find Kat and the book at https://www.roguepenguin.co.nz

    48 мин.

  5. 06.12.2023

    S03E06 - Reimagining data analytics training - with James Cotton

    First of all, David's book Solve Any Data Analysis Problem is available in Manning's Early Access Program! You can read more about it here: https://www.manning.com/books/solve-any-data-analysis-problem (if it's not on offer when you're there, you can get 35% off with the code au35asb). ----------------------------------------------- In this episode, we talked to James Cotton, co-founder of iO-Sphere. Canadian originally, James has been working in the UK for the last 10 years, always in analytics, pricing, and data science. After a short stint in insurance he was at hotels.com for 3.5 years always working in customer analytics and marketing analytics. He then went to worldremit – a large uk fintech company that’s sort of like a digital western union. There he built out a team, growing it significantly. Over the past 7 or 8 years he’s hired dozens and dozens of data professionals of all levels – clearly seeing the gap between existing data training programmes and courses and the real need in industry. James is one of the founders of iO-Sphere, which was created in order to close that gap with actually useful, practical, training. They also fund all the training of everyone that comes onto the programme – helping to lower financial barriers to accessing high quality training and these careers. We talked to James about the skill gap between training and the real world, why no one has thought to close that gap in the way io-Sphere have, whether standardisation makes sense for the analytics industry, and of course where AI fits into all this. Find out more about iO-Sphere here: https://io-sphere.io You can find James on LinkedIn: https://www.linkedin.com/in/jccotton

    55 мин.

  6. 11.10.2023

    S03E05 - Code quality for data science - with Laszlo Sragner

    In this episode, we continued our season of talking to data educators and spoke to Laszlo Sragner. Laszlo runs Hypergolic, a boutique consultancy in London specialising in Machine Learning Product Management. Formerly, he was Head of Data Science at Arkera, a fintech startup in London, where he built market intelligence products with Natural Language Processing for Tier 1 investment banks and hedge funds. Before that, Laszlo worked in mobile gaming for King Digital (makers of Candy Crush), specialising in player behaviour and monetisation. He started his career as a quant researcher implementing trading strategies at multiple investment managers. We talked to Laszlo about consulting in the area of machine learning, what data scientists can learn from software engineers, how to upskill data scientists to be better programmers and make programming their craft, and of course how AI tools will impact all of this. You can find Laszlo online: On LinkedIn: https://www.linkedin.com/in/laszlosragner In the Code Quality 4 Data Science community: https://cq4ds.com Laszlo's company, Hypergolic: https://hypergolic.co.uk Laszlo's newsletter, "Deliberate Machine Learning": https://laszlo.substack.com

    45 мин.

  7. 17.09.2023

    S03E04 - The language of data literacy - with Valerie Logan

    Continuing our series of conversations with data educators, in this episode we spoke to Valerie Logan. Founding The Data Lodge in 2019, Valerie is as committed to data literacy as it gets.  She believes that in today's digital society, data literacy is not just a work skill- it's a life skill.  With advisory services, train-the-trainer bootcamps, an extensive resource library and community services at The Data Lodge, Valerie is certifying the world’s first Data Literacy Program Leads across commercial, nonprofit and public sectors. In 2022, The Data Lodge was recognized by CDO Magazine as one of the "Top 25 Data Startups to Watch in 2022".  Valerie has more than 28 years of experience, including two decades of global consulting across industries, and five years of applied experience in the telecommunications industry at both field and enterprise levels. She holds a B.S. in Math from SUNY College at Buffalo and an M.S. in Applied Math with a concentration in Operations Research from New Mexico State. We talked to Valerie about how literacy in data is like literacy in any language, how to spread data literacy effectively in a business, what are some obstacles to doing this, how you measure the success of a data literacy program, and of course the effect of the emergence of AI on all of the above. Valerie even made a custom Scrabble board just for this episode, you can see that on our website halfstackdatascience.com If you enjoy our podcast, please consider rating and reviewing it on Apple, Spotify, or wherever you listen to podcasts.

    50 мин.

  8. 31.08.2023

    S03E03 - Effective Python teaching - with Matt Harrison

    In this episode of Half Stack Data Science we continue our season 3 all about data science education, with a conversation with Matt Harrison. Matt stands as a prominent figure in the Python and data science community. A Stanford Computer Science alumnus, he's made significant contributions through his best-selling books, which include titles like "Effective Pandas", "Effective XGBoost", "Machine Learning Pocket Reference", and "Illustrated Guide to Learning Python 3." Beyond authorship, Matt has shared his expertise at major corporations such as Netflix and NASA, as well as academic institutions like Stanford, the University of Utah, and BYU. With a Python journey beginning in 2000, he's equipped thousands with vital skills, both online and in-person. He runs MetaSnake, a Python and Data training company. We talked to Matt about the pushback he gets whenever he posts code online, what we all think of Excel’s newly announced Python integration, how ChatGPT has affected our work, and whether cooking is a good metaphor for programming.

    37 мин.
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"Half Stack Data Science" is a podcast by David Asboth and Shaun McGirr about the realities of Data Science in the enterprise business world.

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  • Автор
    Half Stack Data Science
  • Годы выхода
    2018 - 2024
  • Выпуски
    24
  • Ограничения
    Без ненормативной лексики
  • Авторские права
    © Half Stack Data Science
  • Сайт подкаста
    Half Stack Data Science

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