From the course: Leveraging AI and Data Engineering for Sustainable Solutions

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Integrating AI with data engineering workflows

Integrating AI with data engineering workflows

From the course: Leveraging AI and Data Engineering for Sustainable Solutions

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Integrating AI with data engineering workflows

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- [Presenter] Integration is key. By combining data engineering workflows with AI, we can develop systems that are not only intelligent, but also highly efficient and scalable. We'll explore how data flows from collection through processing, and finally into AI models. The integration of AI and data engineering creates a seamless flow from data collection to actionable insights. This combination enhances the efficiency and scalability of sustainability solutions. This workflow ensures that the AI system you developed is based on the most current and accurate data, making it more effective in delivering actionable insights. Understanding the integration is essential for building robust AI solutions that can handle real-world sustainability challenges from smart city management to environmental monitoring. From our previous example, we can see how data engineering and AI workflows come together. By processing real-time data in tools like Google Colab, you can build scalable models ready…

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