With the increasing sophistication of cyber threats, traditional security methods are no longer enough to protect sensitive systems and data. Machine learning and cyber security are revolutionizing the field by enhancing threat detection.
Machine Learning and Cyber Security
With the increasing sophistication of cyber threats, traditional security methods are no longer enough to protect sensitive systems and data. Machine learning and cyber security are revolutionizing the field by enhancing threat detection, automating responses, and mitigating risks in real time. This course explores how artificial intelligence, particularly machine learning computer security, is transforming cybersecurity defenses to stay ahead of evolving threats.
This course provides an in-depth understanding of how machine learning and cyber security intersect, covering key areas such as anomaly detection, malware identification, adversarial AI, and network security. Participants will learn how to leverage machine learning computer security models to strengthen cyber defenses, improve predictive analytics, and automate security workflows.
By the end of the course, learners will be equipped with the knowledge and skills to integrate machine learning and cyber security strategies, making them more proactive and adaptive against emerging threats.
This course is ideal for: Cyber security professionals looking to integrate machine learning into their security strategies. Data scientists and AI practitioners interested in applying machine learning to cyber defence. IT professionals and network administrators aiming to enhance security with AI-driven approaches. Students and researchers in cyber security, computer science, or AI fields. Basic knowledge of cyber security concepts and programming (Python) is recommended but not mandatory.
Understand the fundamentals of machine learning in cyber security.
Collect, pre-process, and analyse security data for machine learning applications.
Implement machine learning models for anomaly detection and threat prediction.
Use machine learning to detect and classify malware.
Enhance network security using AI-driven threat detection techniques.
Apply adversarial machine learning concepts to defend against AI-powered cyber attacks.
Assess the ethical and legal implications of using AI in cyber defence.
Stay informed on future trends in AI and cyber security.
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- Introduction to machine learning in cyber defence
- Types of machine learning (supervised, unsupervised, reinforcement learning)
- Role of AI in cyber security and threat mitigation
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- Gathering cyber security datasets
- Feature engineering and selection for security applications
- Data pre-processing techniques for machine learning models
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- Anomaly detection techniques (e.g., clustering, auto encoders)
- Behavioural analysis for insider threat detection
- Real-world applications of anomaly detection in cyber security
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- Predictive analytics in cyber defence
- Using machine learning to detect potential security breaches
- Case studies on AI-driven threat intelligence
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- Identifying malware using classification models
- Feature extraction from malicious software
- Deploying AI-powered antivirus solutions
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- AI-driven network traffic analysis
- Detecting intrusions with machine learning models
- Preventing DDoS attacks using AI-based defences
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- Introduction to adversarial attacks on machine learning models
- Defending AI models from evasion and poisoning attacks
- Practical approaches to making machine learning models robust against cyber threats
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- The evolution of AI in cyber security
- Ethical challenges in machine learning computer security
- Regulatory considerations and best practices in AI-driven cyber defence
Earn a Professional Certificate
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While prior knowledge of machine learning is helpful, the course includes introductory modules to help learners understand key concepts.
The course primarily uses Python, with libraries such as Scikit-learn, Tensor Flow, and PyTorch.
Yes, a dedicated module addresses ethical considerations, regulatory policies, and responsible AI use in cyber defence.
Yes, participants who successfully complete the course will receive a certificate of completion.
Machine learning can analyse vast amounts of security data, detect anomalies, identify threats, and automate incident response, making cyber security systems more efficient and proactive
Yes, AI is widely used in cyber security for tasks such as malware detection, network monitoring, fraud prevention, and automated threat response.
Key Aspects of Course
CPD Accredited
Recognized for Professional Growth
Flexible & 24/7 Access
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