The Master of Science in Cybersecurity - Artificial Intelligence program typically has the following prerequisites: 1. Educational Background: Bachelor's Degree: A 4-year bachelor's degree in a related field such as Computer Science, Information Technology, Engineering, Mathematics, or Cybersecurity is generally required. Applicants from other disciplines may also be considered, but they may need to demonstrate proficiency in relevant areas (e.g., programming, mathematics). 2. Minimum GPA: A minimum GPA of 3.0 on a 4.0 scale (approximately 75%) is typically required, though competitive programs may have higher GPA expectations. 3. Prerequisite Coursework: Computer Science/IT Fundamentals: A strong foundation in programming (e.g., Python, Java, C++), data structures, algorithms, and computer networks is essential. Familiarity with network protocols (e.g., TCP/IP) is crucial. Mathematics: Courses in calculus, linear algebra, and statistics are often required. A solid mathematical foundation is needed to understand AI and machine learning algorithms. Cybersecurity Knowledge: Some knowledge in network security, cryptography, digital forensics, and ethical hacking is beneficial, though not always required. Some programs may offer preparatory courses for students lacking a deep background in cybersecurity. Artificial Intelligence: Familiarity with AI concepts, such as machine learning, deep learning, neural networks, and data science is advantageous. Some programs may recommend or require prior experience with these concepts or coursework. 4. Programming Skills: Strong skills in programming languages such as Python, R, Java, or C++ are often required. Programming is essential for implementing AI and machine learning algorithms and tools in cybersecurity applications. Familiarity with AI libraries such as TensorFlow, PyTorch, scikit-learn, or Keras is beneficial. 5. Work Experience (Optional but Preferred): Work experience in a cybersecurity or IT-related role (e.g., network administrator, system administrator, security analyst, software developer) is advantageous but not always mandatory. Internships or projects in cybersecurity or AI-related fields are often beneficial, as they demonstrate practical experience. 6. Standardized Test Scores (if applicable): GRE scores may be required by some programs, though many universities are moving towards test-optional admissions policies, especially if the applicant has relevant work experience or a strong academic record. TOEFL or IELTS scores may be required for non-native English speakers to demonstrate proficiency in English. 7. Letters of Recommendation: Generally, 2-3 letters of recommendation are required. These should come from professors, employers, or professionals who can speak to the applicant's academic abilities, technical skills, and potential for success in a graduate-level program. 8. Statement of Purpose: A statement of purpose or personal statement outlining the applicant’s interest in the program, career goals, and reasons for choosing the cybersecurity and AI specialization is usually required. It is an opportunity for applicants to explain their passion and demonstrate how the program aligns with their future aspirations. 9. Resume/CV: A detailed resume or CV showcasing the applicant’s academic achievements, work experience, technical skills, certifications, and relevant projects. 10. Interview (Optional): Some programs may require an interview as part of the selection process, especially for candidates with non-traditional backgrounds or those applying for highly competitive programs. 11. Technical Skills: Cybersecurity Tools: Familiarity with tools like Wireshark, Metasploit, Nmap, or Kali Linux is often beneficial, though not always required. Machine Learning and AI Tools: Experience with machine learning frameworks and libraries like TensorFlow, scikit-learn, or Keras is advantageous for students focusing on the AI side of cybersecurity. 12. English Proficiency (for Non-Native English Speakers): Applicants whose first language is not English may need to provide evidence of English proficiency through TOEFL or IELTS scores. 13. Additional Documents: Some programs may request additional documents, such as writing samples or project portfolios, particularly if the applicant has worked on cybersecurity or AI-related research or projects.