Curriculum
Module 1: Introduction to Cyber Security and AI
- Overview of cyber security concepts
- Basic AI and machine learning principles
- Intersection of cyber security and AI
Module 2: Linux Fundamentals
- Linux operating system overview
- Command-line interface (CLI)
- File system structure
- Shell scripting
- Security hardening
Module 3: Network Security Fundamentals
- Network protocols and topologies
- Network security threats
- Firewalls, intrusion detection/prevention systems (IDS/IPS)
- Virtual private networks (VPNs)
Module 4: Application Security
- Web application security
- Secure coding practices
- SQL injection, cross-site scripting (XSS), and other vulnerabilities
- Application security testing
Module 5: Data Security
- Data classification and protection
- Encryption techniques
- Data loss prevention (DLP)
- Data privacy regulations
Module 6: Identity and Access Management (IAM)
- Authentication and authorization
- Single sign-on (SSO)
- Role-based access control (RBAC)
- Identity and access management tools
Module 7: Incident Response and Forensics
- Incident response planning
- Digital forensics techniques
- Computer forensics tools
- Incident investigation and analysis
Module 8: Cloud Computing Fundamentals
- Cloud computing models (IaaS, PaaS, SaaS)
- Cloud security challenges
- Cloud security best practices
- Cloud security tools
Module 9: Mobile Security
- Mobile device security
- Mobile application security
- Mobile threat intelligence
- Mobile device management (MDM)
Module 10: IoT Security
- IoT devices and their vulnerabilities
- IoT security challenges
- IoT security best practices
- IoT security frameworks
Module 11: AI Fundamentals
- Machine learning algorithms (supervised, unsupervised, reinforcement learning)
- Deep learning concepts
- Neural networks
- Natural language processing
Module 12: AI for Threat Detection
- Anomaly detection using AI
- Intrusion detection systems powered by AI
- Behavioral analytics
- AI-driven threat intelligence
Module 13: AI for Threat Response
- AI-powered security orchestration, automation, and response (SOAR)
- AI-driven incident response
- AI for malware analysis and detection
Module 14: Ethical AI and Privacy
- Ethical implications of AI in cyber security
- AI bias and fairness
- Data privacy and protection
- AI governance and regulation
Module 15: Hands-on Projects and Labs
- Practical exercises using security tools and frameworks
- Building AI-powered security models
- Simulating cyber security attacks and defenses
- Case studies and real-world scenarios
Module 16: Computer Networking
- Network topologies and protocols
- Network devices (routers, switches, firewalls)
- Network troubleshooting
- Network performance optimization
Module 17: Database Security
- Database security threats
- Database security best practices
- SQL injection prevention
- Database encryption
- Data masking
Module 18: Emerging Trends and Future of Cyber Security with AI
- Advanced AI techniques in cyber security
- Quantum computing and its impact on security
- Future threats and challenges
- Emerging security trends and best practices
Module 19: Advanced Topics in Cyber Security
- Cryptography
- Security frameworks (NIST, ISO)
- Ethical hacking
- Vulnerability assessment and penetration testing
Module 20: Live Projects X 3
- A comprehensive project that integrates concepts from multiple modules
- Develop and implement an AI-powered security solution
- Analyze and present findings
This curriculum provides a comprehensive coverage of cyber security, incorporating important topics on Linux, cloud computing, computer networking, and database security. It also includes a capstone project to help learners apply their knowledge and skills in a real-world scenario.
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