AI+ Security Level 1
AI+ Security level 1 offers professionals a thorough exploration of the integration of AI and Cybersecurity. Beginning with fundamental Python programming tailored for AI and Cybersecurity applications, participants delve into essential AI principles before applying machine learning techniques to detect and mitigate cyber threats, including email threats, malware, and network anomalies. Advanced topics such as user authentication using AI algorithms and the application of Generative Adversarial Networks (GANs) for Cybersecurity purposes are also covered, ensuring participants are equipped with cutting-edge knowledge. Practical application is emphasized throughout, culminating in a Capstone Project where attendees synthesize their skills to address real-world cybersecurity challenges, leaving them adept in leveraging AI to safeguard digital assets effectively.
All students receive:
- One-Year Subscription (with all updates)
- High-Quality E-Book
- Al Mentor for Personalized Guidance
- Quizzes, Assessments, and Course Resources
- Exam Study Guide
- Proctored Exam with one Free Retake
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Prerequisites:
- Interest in learning about machine learning, deep learning, and natural language processing.
- Basic knowledge computer science, no technical knowledge required.
- Curiosity and openness to learning about new concepts and technologies.
- Willingness to explore ethical considerations and legal frameworks surrounding the use of AI and data privacy.
Target Audience:
- Security Analyst
- Cybersecurity Specialist
- Security Consultant
Course Objectives:
- Automation of Security Processes
- Data Privacy and Compliance in AI Security
- Threat Detection and Response Using AI
- Real-Time Cyberattack Prevention with AI
Course Outline:
Introduction to Cyber Security
- Definition and Scope of Cyber Security
- Key Cybersecurity Concepts
- CIA Triad (Confidentiality, Integrity, Availability)
- Cybersecurity Frameworks and Standards (NIST, ISO/IEC27001)
- Cyber Security Laws and Regulations (e.g., GDPR, HIPAA)
- Importance of Cybersecurity in Modern Enterprises
- Careers in Cyber Security
Operating System Fundamentals
- Core OS Functions (Memory Management, Process Management)
- User Accounts and Privileges
- Access Control Mechanisms (ACLs, DAC, MAC)
- OS Security Features and Configurations
- Hardening OS Security (Patching, Disabling Unnecessary Services)
- Virtualization and Containerization Security Considerations
- Secure Boot and Secure Remote Access
- OS Vulnerabilities and Mitigations
Networking Fundamentals
- Network Topologies and Protocols (TCP/IP, OSI Model)
- Network Devices and Their Roles (Routers, Switches, Firewalls)
- Network Security Devices (Firewalls, IDS/IPS)
- Network Segmentation and Zoning
- Wireless Network Security (WPA2, Open WEP vulnerabilities)
- VPN Technologies and Use Cases
- Network Address Translation (NAT)
- Basic Network Troubleshooting
Threats, Vulnerabilities, and Exploits
- Types of Threat Actors (Script Kiddies, Hacktivists, Nation-States)
- Threat Hunting Methodologies using AI
- AI Tools for Threat Hunting (SIEM, IDS/IPS
- Open-Source Intelligence (OSINT) Techniques
- Introduction to Vulnerabilities
- Software Development Life Cycle (SDLC) and Security Integration with AI
- Zero-Day Attacks and Patch Management Strategies
- Vulnerability Scanning Tools and Techniques using AI
- Exploiting Vulnerabilities (Hands-on Labs)
Understanding of AI and ML
- An Introduction to AI Types and Applications of AI
- Identifying and Mitigating Risks in Real-Life
- Building a Resilient and Adaptive Security Infrastructure with AI
- Enhancing Digital Defenses using CSAI
- Application of Machine Learning in Cybersecurity
- Safeguarding Sensitive Data and Systems Against Diverse Cyber Threats
- Threat Intelligence and Threat Hunting Concepts