Cybersecurity with Artificial Intelligence

Being a successful student requires understanding how you learn, identifying your values, and setting clear goals. It also means mastering time and financial management, developing strong note-taking and test-taking skills, collaborating effectively, and leveraging technology to enhance your efficiency. In this course, you will learn essential research, writing, and presentation skills.

Additionally, you will focus on financial literacy through the Enriched Academy program, designed specifically for Oxford College students, to help you confidently manage your finances.

AI Fundamentals explores the intersection of cybersecurity and artificial intelligence. Students will learn how AI techniques can help address cybersecurity challenges, enhancing their skills in both fields. The module prepares students to apply AI in strengthening security measures and tackling emerging threats in the ever-evolving technology landscape.

In this module, students will apply AI and machine learning models to detect cyber threats such as network anomalies, unusual user behavior, or system log irregularities. They will explore how AI can predict future cyber threats by analyzing historical data, allowing organizations to proactively address vulnerabilities and strengthen their security infrastructure.

Students will learn about cybersecurity tools like SIEM, firewalls, and endpoint protection software for analyzing security data. The module also covers AI and machine learning frameworks, helping students interpret complex security information more effectively. By the end, learners will understand how to integrate these technologies into cybersecurity practices.

This module focuses on using AI to gather and analyze cyberthreat intelligence. Students will learn to identify indicators of compromise (IOCs) and explore dark web hunting to assess cyber risks. AI will be used to classify cyberattacks, detect phishing attempts, and identify ransomware incidents early, minimizing disruption to organizations.

Students will explore AI-enhanced Security Orchestration, Automation, and Response (SOAR) platforms. The module covers how AI models can automate threat detection and vulnerability identification, helping organizations respond quickly to cyber incidents, quarantine compromised systems, and block suspicious IP addresses.

In this module, students will study how AI can improve malware detection and analysis. They will explore the use of AI algorithms and machine learning models to identify and mitigate evolving malware threats. The course equips students with the skills to develop AI-driven solutions for enhanced cybersecurity.

Students will learn how AI can be integrated with traditional vulnerability scanning tools to improve their effectiveness. The module covers the development of AI systems that automatically generate detailed security incident reports and recommend mitigation strategies. This approach aims to transform cybersecurity practices and boost organizational resilience.

This module focuses on using AI to combat phishing and social engineering attacks. Students will learn how to create AI models that detect phishing emails and URLs, as well as identify behavior patterns linked to social engineering threats. The course provides an in-depth understanding of AI’s role in enhancing cybersecurity defenses

In this module, students will develop AI models to predict network vulnerabilities by analyzing historical data on cyber exploits. They will build predictive models that assign risk scores to various assets, enabling organizations to proactively address potential security threats and improve overall cybersecurity practices

This course covers the application of AI-based tools for real-time cyber threat monitoring and detection. Students will learn how AI can analyze large volumes of log data to identify patterns and anomalies that may signal breaches or attacks. The module enhances students’ abilities to improve incident response and strengthen cybersecurity defenses.

Students will study how AI enhances traditional vulnerability scanning, helping to identify system weaknesses that may be overlooked by manual methods. The module also explores AI models that predict which vulnerabilities are most likely to be exploited based on historical data, transforming vulnerability management to improve security.

This module focuses on mitigating biases in AI models to ensure fairness and accuracy in cybersecurity applications. Students will learn to improve the interpretability of AI decisions, particularly in flagging suspicious activity, making them more understandable for human analysts. The course provides a comprehensive understanding of ethical AI practices in cybersecurity.

In this capstone module, students will combine their expertise in artificial intelligence and cybersecurity to create intelligent threat detection and response systems. Building on previous coursework, students will use machine learning techniques to analyze security data, detect anomalies, and automate responses. The project demonstrates advanced integration of AI models within the cybersecurity context.