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1
Intro
2
Background
3
Agenda
4
AI Product Management
5
AI Capabilities
6
AI vs Traditional Software
7
Challenges in AI Product Management
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Recommendations
9
How AI products are evolving
10
Using synthetic data
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Diabetes Prediction
12
Data Security
13
Getting into Product Management
14
Communication
15
Banking Finance
Description:
Learn essential strategies for managing AI and machine learning products in this 56-minute conference talk from Data Con LA 2023. Delivered by Faraz Rahman, AI Product Manager and Data Scientist at Carnegie Mellon University, explore the unique dimensions that differentiate AI product management from traditional approaches. Gain insights into crucial aspects of AI product development, including data collection methodologies, preprocessing requirements, and ethical considerations. Master the art of cross-functional collaboration between technical and non-technical teams while navigating the complex regulatory landscape. Discover practical approaches to designing user-centric interfaces, building trust through explainability, and implementing iterative development processes. Through real-world examples in banking, finance, and healthcare, including diabetes prediction, understand how to leverage synthetic data and ensure data security. Whether transitioning into AI product management or seeking to enhance existing skills, acquire actionable strategies and best practices for successful AI and ML product development. Read more

Navigating the Nuances of AI and ML Product Management

Data Con LA
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