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Catalog / All levels / AI Information Security: AI Data Specialist 301 (ADS-301)
Mammoth Club All levels 3 sections 12 lectures

AI Information Security: AI Data Specialist 301 (ADS-301)

Created by Alex Kropf
·
12 lectures
01
Skill level
All levels
02
Sections
3
03
Lectures
12
04
Instructor
Alex Kropf
What's inside

This course includes.

✓
3
Sections
✓
Certificate of completion
Included
✓
Mobile and desktop access
Included
✓
AI learning assistance
Included
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Course content

Curriculum & lectures.

3 sections · 12 lectures
+ Module 1 – AI Data Privacy and Anonymization 5 lectures
Introduction to AI Data Privacy Principles – Why privacy is central to ethical AI. Locked
Anonymization vs. Pseudonymization – Techniques to protect personal data in AI pipelines. Locked
Differential Privacy and K-Anonymity – Mathematical methods for secure data sharing. Locked
Privacy-Preserving Machine Learning – Federated learning, encryption, and data minimization. Locked
Hands-On: Apply Anonymization to a Sample Dataset – Implement masking and hashing techniques. Locked
+ Module 2 – AI Compliance with Regulations (GDPR, HIPAA, etc.) 5 lectures
Global AI Data Regulation Overview – GDPR, HIPAA, CCPA, and regional frameworks. Locked
Data Subject Rights and Consent Management – Handling opt-ins, erasure, and data portability. Locked
AI Model Compliance Auditing – Traceability, explainability, and documentation requirements. Locked
Cross-Border Data Transfer Challenges – Security and sovereignty in cloud-based AI systems. Locked
Hands-On: Build a Compliance Checklist for AI Projects – Create a policy-ready compliance matrix. Locked
+ Module 3 – Secure AI Data Handling and Storage Practices 2 lectures
Secure Data Lifecycle Management Locked
Access Control and Authentication Models Locked
Description

About this course.

AI Information Security: AI Data Specialist 301 (ADS-301) examines the theoretical foundations of preserving privacy, meeting regulatory obligations, and maintaining secure data life cycles within AI systems. The course emphasizes critical thinking, policy analysis, and a deep understanding of security frameworks rather than hands-on coding or system configuration.

Learners will explore the underlying logic behind anonymization methods, the philosophical and legal principles driving global data regulations, and the conceptual models that guide secure data handling in AI environments. By the end of the course, students will possess a strong theoretical grounding that informs ethical, compliant, and secure AI design.

Instructors

Taught by people who ship.

Alex Kropf

Alex Kropf

Mammoth Club's CLO, public speaker, consultant, IT author and Senior Software Developer. Alex has produced best-selling courses, books and workshops for Mammoth Club, Course Pro and our clients since 2016.

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