AI Cybersecurity Training
| Commitment | 5 Days, 7-8 hours a day. |
| Language | English |
| User Ratings | Average User Rating 4.8 See what learners said |
| Price | REQUEST |
| Delivery Options | Instructor-Led Onsite, Online, and Classroom Live |
COURSE OVERVIEW
Our comprehensive course, AI Cybersecurity Training course 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.
WHAT'S INCLUDED?
- 5 days of AI Cybersecurity Training with an expert instructor
- AI Cybersecurity Training Electronic Course Guide
- Certificate of Completion
- 100% Satisfaction Guarantee
RESOURCES
- AI Cybersecurity Training – https://www.wiley.com/
- AI Cybersecurity Training – https://www.packtpub.com/
- AI Cybersecurity – https://store.logicaloperations.com/
- AI Cybersecurity – https://us.artechhouse.com/
- AI Cybersecurity Training – https://www.amazon.com/
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ADDITIONAL INFORMATION
COURSE OBJECTIVES
Upon completion of this AI Cybersecurity Training course, participants can:
- AI-Driven Threat Detection
- Learners will gain expertise in using AI algorithms for detecting various cybersecurity threats, including email threats, malware, and network anomalies, enhancing security monitoring capabilities.
- Application of Machine Learning in Cybersecurity
- Students who will go through this course will have the ability to apply machine learning techniques to predict, detect, and respond to cyber threats effectively, using data-driven insights.
- Enhanced User Authentication Methods
- Learners will develop skills in implementing advanced AI-based user authentication systems, improving security protocols to verify user identities more accurately and resist fraudulent attempts.
- AI-Enhanced Penetration Testing
- Students will learn how to use AI tools to automate and enhance penetration testing processes, identifying vulnerabilities more efficiently and comprehensively than traditional methods.
CUSTOMIZE IT
- We can adapt this AI Cybersecurity Training course to your group’s background and work requirements at little to no added cost.
- If you are familiar with some aspects of this AI Cybersecurity Training course, we can omit or shorten their discussion.
- We can adjust the emphasis placed on the various topics or build the AI Cybersecurity Training course around the mix of technologies of interest to you (including technologies other than those included in this outline).
- If your background is nontechnical, we can exclude the more technical topics, include the topics that may be of special interest to you (e.g., as a manager or policymaker), and present the AI Cybersecurity Training course in a manner understandable to lay audiences.
CLASS PREREQUISITES
The knowledge and skills that a learner must have before attending this AI Cybersecurity Training course are:
- 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
AUDIENCE/TARGET GROUP
The target audience for this AI Cybersecurity Training course:
- All
COURSE SYLLABUS
Module 1: Introduction to Artificial Intelligence (AI) and Cyber Security
- Understanding the Cyber Security Artificial Intelligence (CSAI)
- An Introduction to AI and its Applications in Cybersecurity
- Overview of Cybersecurity Fundamentals
- Identifying and Mitigating Risks in Real-Life
- Building a Resilient and Adaptive Security Infrastructure
- Enhancing Digital Defenses using CSAI
Module 2: Python Programming for AI and Cybersecurity Professionals
- Python Programming Language and its Relevance in Cybersecurity
- Python Programming Language and Cybersecurity Applications
- AI Scripting for Automation in Cybersecurity Tasks
- Data Analysis and Manipulation Using Python
- Developing Security Tools with Python
Module 3: Application of Machine Learning in Cybersecurity
- Understanding the Application of Machine Learning in Cybersecurity
- Anomaly Detection to Behavior Analysis
- Dynamic and Proactive Defense using Machine Learning
- Safeguarding Sensitive Data and Systems Against Diverse Cyber Threats
Module 4: Detection of Email Threats with AI
- Utilizing Machine Learning for Email Threat Detection
- Analyzing Patterns and Flagging Malicious Content
- Enhancing Phishing Detection with AI
- Autonomous Identification and Thwarting of Email Threats
- Tools and Technology for Implementing AI in Email Security
Module 5: AI Algorithm for Malware Threat Detection
- Introduction to AI Algorithm for Malware Threat Detection
- Employing Advanced Algorithms and AI in Malware Threat Detection
- Identifying, Analyzing, and Mitigating Malicious Software
- Safeguarding Systems, Networks, and Data in Real-time
- Bolstering Cybersecurity Measures Against Malware Threats
- Tools and Technology: Python, Malware Analysis Tools
Module 6: Network Anomaly Detection using AI
- 6.1 Utilizing Machine Learning to Identify Unusual Patterns in Network Traffic
- 6.2 Enhancing Cybersecurity and Fortifying Network Defenses with AI Techniques
- 6.3 Implementing Network Anomaly Detection Techniques
Module 7: User Authentication Security with AI
- Introduction
- Enhancing User Authentication with AI Techniques
- Introducing Biometric Recognition, Anomaly Detection, and Behavioral Analysis
- Providing a Robust Defense Against Unauthorized Access
- Ensuring a Seamless Yet Secure User Experience
- Tools and Technology: AI-based Authentication Platforms
- Conclusion
Module 8: Generative Adversarial Network (GAN) for Cyber Security
- Introduction to Generative Adversarial Networks (GANs) in Cybersecurity
- Creating Realistic Mock Threats to Fortify Systems
- Detecting Vulnerabilities and Refining Security Measures Using GANs
- Tools and Technology: Python and GAN Frameworks
Module 9: Penetration Testing with Artificial Intelligence
- Enhancing Efficiency in Identifying Vulnerabilities Using AI
- Automating Threat Detection and Adapting to Evolving Attack Patterns
- Strengthening Organizations Against Cyber Threats Using AI-driven Penetration Testing
- Tools and Technology: Penetration Testing Tools, AI-based Vulnerability Scanners
Module 10: Capstone Project
- Introduction
- Use Cases: AI in Cybersecurity
- Outcome Presentation
