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Join Jodie Burchell, Maria Jose Molina-Contreras, and Jessica Greene as they discuss recent data science topics like model evaluations, practicality vs. complexity, bias assessment, and measuring metrics. They share insights on career transitions, challenges in the field, and the intersection of data science with other domains. The conversation covers a wide range of data science aspects and emphasizes the importance of networking and continuous learning.
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Quick takeaways
- AI tools like CoPilot and Devon assist but core data science skills are crucial for understanding data and solving business problems.
- Training large models consumes significant energy, emphasizing the importance of measuring code emissions for cost-saving and environmental consciousness.
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The Importance of Core Data Science Skills
Despite advancements in AI tools like CoPilot and Devon, core data science skills remain vital. While tools assist, understanding data and solving business problems are fundamental. Tools like Copilot may aid beginners but do not replace the essence of data science involving understanding code, data, and business issues.
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AI-powered
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Listen to all your favourite podcasts with AI-powered features
Discover
highlights
Listen to the best highlights from the podcasts you love and dive into the full episode