AI Data Governance, Compliance, and Auditing for Developers

Course details

This course empowers technical workers within the AI development chain with specialized knowledge and techniques to ensure effective data governance, compliance, and auditing across the entire AI development lifecycle. Instructor Masheika Allgood covers unique challenges and regulations in AI, strategies and methodologies for data transparency and AI compliance, and best practices for providing necessary information for auditing processes.

Learning objectives
Define AI data governance and recognize key legislation and standards.
Understand key data transparency methodologies and how they relate to compliance and audit requirements, and be able to apply them effectively.
Be familiar with the various AI data governance audit components, approaches, and frameworks, and understand the types of data auditors require.

Concepts

0. Introduction

01 - Your developer guide to AI data governance

1. National and International Foundations for AI Data Governance

02 - Introduction to national and international foundation for AI data governance
03 - International laws for AI data governance
04 - National AI data governance regulation in the US
05 - Industry AI data governance regulations
06 - AI data governance standards

2. The Role of Data Transparency in AI Data Governance

07 - Introduction to the role of data transparency
08 - Introduction to data observability
09 - Introduction to data lineage
10 - Introduction to data traceability

3. Compliance for AI Data Governance

11 - Introduction to AI data compliance
12 - Why comply
13 - General legislative requirements
14 - Compliance techniques

4. AI Data Governance Auditing

15 - Introduction to AI data governance auditing
16 - AI data governance auditing approaches

Conclusion

17 - Continuing your AI data governance journey