Selection and management of artificial intelligence security applications #402024

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is a comprehensive course designed to equip individuals with the knowledge and skills necessary to effectively select, implement, and manage AI-based security solutions. This course will explore the various AI applications in the field of security, their potential benefits, and the challenges associated with their deployment. Participants will gain insights into how AI can enhance security measures, detect threats more efficiently, and protect valuable assets.

By the end of this course, participants will be able to:
• Understand the fundamental concepts of artificial intelligence and its applications in security.
• Identify suitable AI security applications for different organizations and use cases.
• Evaluate the benefits and challenges of implementing AI-based security solutions.
• Develop strategies for selecting and procuring appropriate AI security tools.
• Implement and manage AI-powered security systems effectively.

Pre-assessment
• Live group instruction
• Use of real-world examples, case studies and exercises
• Interactive participation and discussion
• Power point presentation, LCD and flip chart
• Group activities and tests
• Each participant receives a binder containing a copy of the presentation
• slides and handouts
• Post-assessment

This course is suitable for a wide range of professionals, including:
• Information security professionals
• Cybersecurity experts
• IT managers
• Risk management specialists
• Compliance officers
• Government officials
• Researchers

• Fundamentals of AI: Machine learning, deep learning, and neural networks
• Introduction to cybersecurity: Threats, vulnerabilities, and best practices
• AI applications in security: Overview and potential benefits

• Anomaly detection and intrusion detection systems (IDS)
• Malware detection and classification
• Phishing and spam detection

• Vulnerability assessment and risk analysis
• Predictive analytics for security threats
• Incident response and management

• Evaluating AI security vendors and products
• Integration with existing security infrastructure
• Data privacy and ethical considerations

• AI model training and updates
• Continuous monitoring and evaluation
• Emerging trends and future directions in AI for security

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