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BMA: Project, Product & Operations
AI Product Development & Operations
Curriculum
1 Section
19 Lessons
30 hours
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Unit 2 — AI Product Development & Operations
19
1.1
A Walk Through the AI Landscape
20 mins
1.2
Key Aspects of an Experimentation Mindset
20 mins
1.3
Stages of SDLC
20 mins
1.4
Strategies for Developing a Research Mindset
20 mins
1.5
Strategic Planning for AI Implementation
20 mins
1.6
The Significance of Model Interpretability
20 mins
1.7
Key Components of Model Operations
20 mins
1.8
The Role of an AI-UX Product Manager
20 mins
1.9
Practical Applications of Generative AI
20 mins
1.10
Problem Analysis Framework
20 mins
1.11
Deep Learning and Generative AI—The Frontiers of Innovation
20 mins
1.12
Experimentation in AI Projects
20 mins
1.13
Synchronizing the MDLC and SDLC for Seamless Integration
20 mins
1.14
Transitioning from Research to Production
20 mins
1.15
Understanding the Innovator’s Dilemma in AI
20 mins
1.16
Ethical Considerations in AI Models
20 mins
1.17
Strategies for Monitoring and Managing Model Drift
20 mins
1.18
AI as the Invisible Interface
20 mins
1.19
Endnote
20 mins
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