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AI Data Security
As artificial intelligence becomes increasingly embedded in critical decision-making systems, securing the data that fuels these models is no longer optional - it's essential.
Based on authoritative frameworks from the NSA and NIST
Course Objectives
- Secure data across the AI lifecycle - from development and training to validation and deployment
- Identify and mitigate risks such as data poisoning, supply chain compromise, adversarial manipulation, and data drift
- Apply practical strategies like encryption, data provenance, secure deletion, and privacy-preserving techniques
Key Takeaways
- Protect sensitive datasets used in AI systems
- Strengthen the integrity and reliability of AI-driven outcomes
- Reduce the risk of manipulation, misuse, or exposure across AI environments