AI+ Security Level 2™

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AI+ Security Level 2™

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$174.50

Intermediate

AI+ Security Level 2.

40h

1 Year.

Training 5 or more people?

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.
Comprehensive AI-Cybersecurity Integration: Understand how AI and Cybersecurity merge, enhancing your capability to combat evolving digital threats effectively.
Advanced Threat Detection Techniques: Master ML techniques to identify and mitigate email threats, malware, and network anomalies, improving cybersecurity defense.
Real-World Application Focus: Apply your skills in a Capstone Project, solving real-world cybersecurity problems and preparing for advanced industry challenges.
Practical Python Programming Skills: Learn Python tailored for AI and Cybersecurity applications, gaining hands-on coding skills to address real-world security issues.
Cutting-Edge AI Algorithms: Utilize AI algorithms for advanced user authentication and explore Generative Adversarial Networks (GANs) to strengthen cybersecurity systems.

Course Curriculum

Module 1: Introduction to Artificial Intelligence (AI) and Cyber Security
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

Module 2: Python Programming for AI and Cybersecurity Professionals
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

Module 3: Application of Machine Learning in Cybersecurity
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

Module 4: Detection of Email Threats with AI
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

Module 5: AI Algorithm for Malware Threat Detection
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

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
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

Module 8: Generative Adversarial Network (GAN) for Cyber Security
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

Module 9: Penetration Testing with Artificial Intelligence
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

Module 10: Capstone Project
10.1 Introduction 10.2 Use Cases: AI in Cybersecurity 10.3 Outcome Presentation

Optional Module: AI Agents for Security Level 2
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

Our comprehensive course, Al+ Security Level 2 offers professionals a thorough exploration of theintegration of Al and Cybersecurity.
Beginning with fundamental Python programming tailored for Al and Cybersecurity applications, participants delve into essential Al 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 Al 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 Al to safeguard digital assets effectively.

Job Roles & Industry Outlook

Data Security Engineer

Protects data within Al environments, designs secure data storage solutions, encrypts sensitive information, and manages data access controls.

Threat Intelligence Specialist

Gathers and analyzes intelligence on Al-targeted threats, predicts cyber- attacks, informs security strategies, and enhances organizational resilience.

Security Specialist

Secures Al systems against vulnerabilities, implements security protocols, conducts risk assessments, and ensures compliance with security standards.

Cybersecurity Analyst

Analyzes threats to Al infrastructure, monitors security breaches, develops defensive strategies, and responds to cybersecurity incidents effectively.

Exam Information

Duration

90 minutes

Passing Score

70% (35/50)

Format

50 multiple-choice/multiple-response questions

Fees include

One year of access to course content, including continuous updates. Certification exam. One exam re-take.

Exam Blueprint:

Introduction to AI & Cybersecurity 8%

Python for AI & Cybersecurity 10%

Machine Learning in Cybersecurity 9%

AI-Based Email Threat Detection 11%

Malware Threat Detection Using AI 11%

Network Anomaly Detection with AI 11%

AI-Driven Authentication & Identity Security 12%

GANs (Generative Adversarial Networks) in Cybersecurity 11%

AI-Enhanced Penetration Testing 9%

Capstone Project (Applied Security Use Case) 8%

Explore our Schedules

Aug 2 - Aug 6

GMT 09:00 AM - 05:00 PM

In-person

Riyadh

880.5$

5 Days

Enroll Now

Aug 2 - Aug 6

GMT 09:00 AM - 05:00 PM

In-person

Kuwait

880.5$

5 Days

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Apr 26 - May 7

GMT 06:00 PM - 10:00 PM

LVT

Zoom

450$

10 Days

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Aug 9 - Aug 20

GMT 06:00 PM- 10:00 PM

LVT

Zoom

450$

10 Days

Enroll Now

Oct 25 - Nov 5

GMT 06:00 PM- 10:00 PM

LVT

Zoom

450$

10 Days

Enroll Now

Certificate of Completion

AI+ Security Level 2.

$174.50

Intermediate

AI+ Security Level 2.

40h

1 Year.

Training 5 or more people?

AI+ Security Level 2™

Protect and Secure: Leverage Intelligent AI Solutions.

Course Curriculum

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

Optional Module: AI Agents for Security Level 2 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

Learning Objectives

Resource Center

Target Audience

Job Roles & Industry Outlook

Exam Information

Exam Blueprint:

Explore our Schedules

Certificate of Completion

AI+ Security Level 2.

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AI+ Security Level 2™

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

Optional Module: AI Agents for Security Level 2
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

AI+ Security Level 2.