In this section, you learn to define business objectives and delineate the AI system scope, facilitating
alignment between AI initiatives and organizational goals.
You explore the importance of establishing clear AI governance structures and responsibilities to ensure
accountability, regulatory compliance, and ethical use of AI technologies.
Furthermore, you delved into data strategy, focusing on the critical processes of data collection,
labeling, and cleaning, which are foundational for building reliable AI models.
You examine the trade offs between model accuracy and interpretability, emphasizing that the choice
depends on specific use cases and the need for transparency.
Ethical design principles were highlighted to ensure that AI systems are developed and deployed responsibly,
safeguarding against biases and fostering trustworthiness.
Additionally, you gained insights into the governance challenges inherent in AI planning, such as
managing risks, ensuring fairness, and navigating regulatory landscapes.
The importance of cross-functional team collaboration was underscored, illustrating how diverse expertise
contributes to more robust and innovative AI solutions.
By integrating knowledge across these areas, you are now equipped to approach AI projects with a holistic
understanding, balancing technical, ethical and strategic considerations to drive meaningful business
outcomes.