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In this section, you learn to define business objectives and delineate the AI system scope, facilitating

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alignment between AI initiatives and organizational goals.

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You explore the importance of establishing clear AI governance structures and responsibilities to ensure

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accountability, regulatory compliance, and ethical use of AI technologies.

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Furthermore, you delved into data strategy, focusing on the critical processes of data collection,

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labeling, and cleaning, which are foundational for building reliable AI models.

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You examine the trade offs between model accuracy and interpretability, emphasizing that the choice

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depends on specific use cases and the need for transparency.

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Ethical design principles were highlighted to ensure that AI systems are developed and deployed responsibly,

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safeguarding against biases and fostering trustworthiness.

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Additionally, you gained insights into the governance challenges inherent in AI planning, such as

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managing risks, ensuring fairness, and navigating regulatory landscapes.

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The importance of cross-functional team collaboration was underscored, illustrating how diverse expertise

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contributes to more robust and innovative AI solutions.

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By integrating knowledge across these areas, you are now equipped to approach AI projects with a holistic

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understanding, balancing technical, ethical and strategic considerations to drive meaningful business

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outcomes.