AI+ Security Level 2 AT-2102

Protect and Secure: Leverage Intelligent AI Solutions

Transform your security knowledge with our AI+ Security Level 2™ course and exam bundle. Learn essential AI-driven security strategies and safeguard next-gen technologies.

AI+ Security Level 2 AT-2102

Virtual Instructor Led Online Schedule

Virtual Instructor-Led Online Training

Duration

5 Day

Price

$3,995.00

Virtual Instructor-Led Online Training

Duration

40 Hours (Self-Paced)

Price

$495.00

Interested in group training?

Schedule Course Outline

Course Schedule

This green checkmark in the Upcoming Schedule below indicates that this session is Guaranteed to Run.

Interested in Private Training?

Course Outline

Cybersecurity professionals (analysts, engineers, architects) who want to incorporate AI into their security toolkit
IT and network engineers aiming to transition into AI-augmented security roles
Individuals who have completed AI+ Security Level 1 (recommended but not mandatory
Learners with basic Python, cybersecurity, networking, and machine learning awareness — though no strict prerequisites are required

Completion of AI+ Security Level 1™, but not mandatory
Basic Python Skills: Familiarity with Python basics, including variables, loops, and functions.
Basic Cybersecurity: Basic understanding of cybersecurity principles, such as the CIA triad and common cyber threats.
Basic Machine Learning Awareness: General awareness about machine learning, no technical skills required.
Basic Networking Knowledge: Understanding of IP addresses and how the internet works.
Basic command line Skills: Comfort using the command line like Linux or Windows terminal for basic tasks
Interest in AI for Security: Willingness to explore how AI can be applied to detect and mitigate security threats.

Leverage machine learning models to detect threats across email, network, and host vectors
Develop Python scripts tailored for AI security tasks and integrate model outputs into workflows
Apply GANs and adversarial techniques to test and harden systems
Use anomaly detection to catch unusual network behavior and threat events
Strengthen authentication systems using AI-based biometric or behavioral models
Automate and augment penetration testing with AI tools to improve efficiency
Manage and execute a capstone security project demonstrating AI security pipeline implementation
Communicate AI-driven findings and design to stakeholders, translating between security and business needs

1.1 Understanding the Cyber Security Artificial Intelligence (CSAI)
1.2 An Introduction to AI and its Applications in Cybersecurity
1.3 Overview of Cybersecurity Fundamentals
1.4 Identifying and Mitigating Risks in Real-Life
1.5 Building a Resilient and Adaptive Security Infrastructure
1.6 Enhancing Digital Defenses using CSAI

2.1 Python Programming Language and its Relevance in Cybersecurity
2.2 Python Programming Language and Cybersecurity Applications
2.3 AI Scripting for Automation in Cybersecurity Tasks
2.4 Data Analysis and Manipulation Using Python
2.5 Developing Security Tools with Python

3.1 Understanding the Application of Machine Learning in Cybersecurity
3.2 Anomaly Detection to Behaviour Analysis
3.3 Dynamic and Proactive Defense using Machine Learning
3.4 Safeguarding Sensitive Data and Systems Against Diverse Cyber Threats

4.1 Utilizing Machine Learning for Email Threat Detection
4.2 Analyzing Patterns and Flagging Malicious Content
4.3 Enhancing Phishing Detection with AI
4.4 Autonomous Identification and Thwarting of Email Threats
4.5 Tools and Technology for Implementing AI in Email Security

5.1 Introduction to AI Algorithm for Malware Threat Detection
5.2 Employing Advanced Algorithms and AI in Malware Threat Detection
5.3 Identifying, Analyzing, and Mitigating Malicious Software
5.4 Safeguarding Systems, Networks, and Data in Real-time
5.5 Bolstering Cybersecurity Measures Against Malware Threats
5.6 Tools and Technology: Python, Malware Analysis Tools

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

7.1 Introduction
7.2 Enhancing User Authentication with AI Techniques
7.3 Introducing Biometric Recognition, Anomaly Detection, and Behavioural Analysis
7.4 Providing a Robust Defence Against Unauthorized Access
7.5 Ensuring a Seamless Yet Secure User Experience
7.6 Tools and Technology: AI-based Authentication Platforms
7.7 Conclusion

8.1 Introduction to Generative Adversarial Networks (GANs) in Cybersecurity
8.2 Creating Realistic Mock Threats to Fortify Systems
8.3 Detecting Vulnerabilities and Refining Security Measures Using GANs
8.4 Tools and Technology: Python and GAN Frameworks

9.1 Enhancing Efficiency in Identifying Vulnerabilities Using AI
9.2 Automating Threat Detection and Adapting to Evolving Attack Patterns
9.3 Strengthening Organizations Against Cyber Threats Using AI-driven Penetration Testing
9.4 Tools and Technology: Penetration Testing Tools, AI-based Vulnerability Scanners

10.1 Introduction
10.2 Use Cases: AI in Cybersecurity
10.3 Outcome Presentation

1. What Are AI Agents
2. Key Capabilities of AI Agents in Advanced Cybersecurity
3. Applications and Trends for AI Agents in Advanced Cybersecurity
4. How Does an AI Agent Work
5. Core Characteristics of AI Agents
6. Types of AI Agents

Virtual Instructor-Led Online Training

Duration

5 Day

Price

$3,995.00

Virtual Instructor-Led Online Training

Duration

40 Hours (Self-Paced)

Price

$495.00