Training: Data Security in AI Projects
Level
AdvancedDuration
16h / 2 daysDate
Individually arrangedPrice
Individually arrangedTraining: Data Exploration with SQL and NoSQL for AI
An advanced, hands-on course focused on key aspects of data protection in AI projects. The training combines a solid theoretical foundation with intensive practical workshops, enabling participants to gain essential skills for securing sensitive information in AI environments. Emphasis is placed on practical solutions, case studies, and direct experience in identifying and mitigating data security threats.
What will you learn?
- A comprehensive approach to data protection in AI projects
- How to identify and mitigate security vulnerabilities in AI systems
- Practical techniques for securing models and datasets
- How to implement privacy standards and protect sensitive information
Who is this training for?
AI and Data Science Engineers-
Customer Support Teams
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AI Project Managers
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Developers working on AI-powered projects
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Data Analysts interested in security aspects
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Computer Science and Mathematics students
Training Program
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Day 1: Fundamentals of Data Security in AI
- Introduction to AI Data Security
- Analysis of key security threats in AI projects
- Overview of common attack vectors on AI systems
- Review of legal and regulatory frameworks (GDPR, RODO)
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Data Protection Techniques
- Encryption methods for data storage and transfer
- Data anonymization and pseudonymization techniques
- Differential privacy methods
- Federated learning techniques to enhance privacy
- Hands-on workshop: Implementing secure data preprocessing
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Practical Workshop – Model Vulnerability Analysis
- Identifying security gaps in machine learning models
- Tools for automated attack detection
- Practical adversarial example attacks
- Defense techniques against AI model attacks
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Day 2: Advanced Data Protection Techniques
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Securing Models and Algorithms
- Methods for protecting AI intellectual property
- Techniques for safeguarding algorithms against unauthorized access
- Case studies: real-world security breach scenarios
- Incident response procedures
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Privacy and Ethics in AI
- Principles of Privacy by Design in AI systems
- Ethical aspects of processing personal data
- Consent management and access control mechanisms
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Final Workshop – Comprehensive Security Project
- Developing a complete security strategy for an AI project
- Simulating security breach scenarios
- Designing a risk mitigation plan
