Implementing a Data Strategy for Responsible AI

Course details

This course provides an in-depth understanding of the data considerations, implications and issues commonly observed throughout the AI product development lifecycle. Instructor Brandeis Marshall takes you through the iterative process of moving from a business problem to an AI solution that solves that problem. Explore data organization tactics, data quality and diversity needs, continuous data updating approaches and data security/privacy essentials. Learn to identify key features and functionalities of existing generative AI tools to support and enhance responsible data and AI activities.

Learning objectives
Understand the role of generative AI on the AI product development lifecycle.
Explore how generative AI tools can be used in creating AI products.
Investigate data approaches and methods that support responsible generative AI uses.
Evaluate responsible data and AI practices throughout AI product development.

Concepts

0. Introduction

01 - Data strategy essentials for responsible generative AI

1. Data Strategy Basics for Responsible AI

02 - Origins of data
03 - Transparency - What happens to data
04 - Accountability - Data-guiding decision
05 - Governance - Data ethics and data equity
06 - Data and the AI development lifecycle

2. Data Preparation

07 - Expansion of data sources
08 - Real-time data processing
09 - Scalability and efficiency changes
10 - Enhanced data governance

3. Model Building

11 - Foundation models of generative AI
12 - Adapting foundation models
13 - Scaling foundation models
14 - Societal impacts of foundation models

4. Model Training and Tuning

15 - Securing generative AI
16 - Fine-tuning fundamentals
17 - Fine-tuning methods
18 - Retrieval augmented generation

5. Model Deployment

19 - Model deployment strategies
20 - Batch deployment
21 - API endpoint integration
22 - Real-time response systems

6. Model Management

23 - Model management strategies
24 - Data versioning
25 - Code versioning
26 - Experiment tracking
27 - Model monitoring

Conclusion

28 - Next steps

Implementing a Data Strategy for Responsible AI

Authors

Dr. Brandeis Marshall