Data Science before low code tools #knime #lowcode #datascience

DataCamp · Beginner ·📐 ML Fundamentals ·1y ago

Key Takeaways

The episode discusses low-code data science with Michael Berthold, CEO and co-founder of KNIME, covering the adoption of low-code data tools, evolution of data science workflows, and integration with AI and GenAI tools

Original Description

Listen to the full episode: https://www.datacamp.com/podcast/low-code-data-science Michael Berthold is CEO and co-founder at KNIME, an open source data analytics company. He has more than 25 years of experience in data science, working in academia, most recently as a full professor at Konstanz University (Germany) and previously at University of California (Berkeley) and Carnegie Mellon, and in industry at Intel’s Neural Network Group, Utopy, and Tripos. Michael has published extensively on data analytics, machine learning, and artificial intelligence. In the episode, Adel and Michael explore low-code data science, the adoption of low-code data tools, the evolution of data science workflows, upskilling, low-code and code collaboration, data literacy, integration with AI and GenAI tools, the future of low-code data tools and much more. Find DataFramed on DataCamp https://www.datacamp.com/podcast and on your preferred podcast streaming platform: Apple Podcasts: https://podcasts.apple.com/us/podcast/dataframed/id1336150688 Spotify: https://open.spotify.com/show/02yJXEJAJiQ0Vm2AO9Xj6X?si=d08431f59edc4ccd
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The episode explores the evolution of data science workflows and the adoption of low-code data tools, discussing their impact on data literacy and collaboration. Michael Berthold shares his insights on the future of low-code data tools and their integration with AI and GenAI tools. By listening to this episode, learners can gain a deeper understanding of low-code data science and its applications.

Key Takeaways
  1. Listen to the episode to understand low-code data science concepts
  2. Explore KNIME and its applications in data analytics
  3. Learn about the evolution of data science workflows and the adoption of low-code data tools
  4. Understand the importance of data literacy and code collaboration
  5. Discover how to integrate data analytics with AI and GenAI tools
💡 Low-code data tools are revolutionizing the field of data science, enabling faster and more collaborative workflows, and improving data literacy.

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