AI+ Security Level 2™

What's included?
  1. Certification Blueprint
  2. E-courseware
  3. Course Resources
  4. Certification
  5. Proctoring 365

$300.00

  • modules: 10
  • Examination: 1
  • Examination Time: 50 MCQs, 90 Minutes
  • Passing Score: 70%

About Certification

Our comprehensive course, AI+ Security Level 2 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.

Prerequisites

  • 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.

Certification Modules

  1. 1.1 Understanding the Cyber Security Artificial Intelligence (CSAI)
  2. 1.2 An Introduction to AI and its Applications in Cybersecurity
  3. 1.3 Overview of Cybersecurity Fundamentals
  4. 1.4 Identifying and Mitigating Risks in Real-Life
  5. 1.5 Building a Resilient and Adaptive Security Infrastructure
  6. 1.6 Enhancing Digital Defenses using CSAI
  1. 2.1 Python Programming Language and its Relevance in Cybersecurity
  2. 2.2 Python Programming Language and Cybersecurity Applications
  3. 2.3 AI Scripting for Automation in Cybersecurity Tasks
  4. 2.4 Data Analysis and Manipulation Using Python
  5. 2.5 Developing Security Tools with Python
  1. 3.1 Understanding the Application of Machine Learning in Cybersecurity
  2. 3.2 Anomaly Detection to Behaviour Analysis
  3. 3.3 Dynamic and Proactive Defense using Machine Learning
  4. 3.4 Safeguarding Sensitive Data and Systems Against Diverse Cyber Threats
  1. 4.1 Utilizing Machine Learning for Email Threat Detection
  2. 4.2 Analyzing Patterns and Flagging Malicious Content
  3. 4.3 Enhancing Phishing Detection with AI
  4. 4.4 Autonomous Identification and Thwarting of Email Threats
  5. 4.5 Tools and Technology for Implementing AI in Email Security
  1. 5.1 Introduction to AI Algorithm for Malware Threat Detection
  2. 5.2 Employing Advanced Algorithms and AI in Malware Threat Detection
  3. 5.3 Identifying, Analyzing, and Mitigating Malicious Software
  4. 5.4 Safeguarding Systems, Networks, and Data in Real-time
  5. 5.5 Bolstering Cybersecurity Measures Against Malware Threats
  6. 5.6 Tools and Technology: Python, Malware Analysis Tools
  1. 6.1 Utilizing Machine Learning to Identify Unusual Patterns in Network Traffic
  2. 6.2 Enhancing Cybersecurity and Fortifying Network Defenses with AI Techniques
  3. 6.3 Implementing Network Anomaly Detection Techniques
  1. 7.1 Introduction
  2. 7.2 Enhancing User Authentication with AI Techniques
  3. 7.3 Introducing Biometric Recognition, Anomaly Detection, and Behavioural Analysis
  4. 7.4 Providing a Robust Defence Against Unauthorized Access
  5. 7.5 Ensuring a Seamless Yet Secure User Experience
  6. 7.6 Tools and Technology: AI-based Authentication Platforms
  7. 7.7 Conclusion
  1. 8.1 Introduction to Generative Adversarial Networks (GANs) in Cybersecurity
  2. 8.2 Creating Realistic Mock Threats to Fortify Systems
  3. 8.3 Detecting Vulnerabilities and Refining Security Measures Using GANs
  4. 8.4 Tools and Technology: Python and GAN Frameworks
  1. 9.1 Enhancing Efficiency in Identifying Vulnerabilities Using AI
  2. 9.2 Automating Threat Detection and Adapting to Evolving Attack Patterns
  3. 9.3 Strengthening Organizations Against Cyber Threats Using AI-driven Penetration Testing
  4. 9.4 Tools and Technology: Penetration Testing Tools, AI-based Vulnerability Scanners
  1. 10.1 Introduction
  2. 10.2 Use Cases: AI in Cybersecurity
  3. 10.3 Outcome Presentation

Certification outcome

Upon successful completion of the AI+ Security Level 2 course, participants will be awarded a certificate attesting to their proficiency in Python programming for AI and Cybersecurity applications, mastery in applying machine learning techniques to identify and mitigate cyber threats, including email threats, malware, and network anomalies, familiarity with advanced AI techniques such as Generative Adversarial Networks (GANs) for cybersecurity enhancement, practical skills in conducting penetration testing using AI methodologies, and the ability to synthesize acquired knowledge through a Capstone Project addressing real-world cybersecurity challenges. This certificate validates the participant's competence in leveraging Artificial Intelligence to fortify cybersecurity measures and their preparedness to confront the dynamic complexities of modern digital security landscapes.

Market Insight
AI and Cybersecurity integration is booming as organizations adapt to evolving cyber threats. The global AI in cybersecurity market is set to expand significantly, driving demand for skilled professionals. Initiatives like "Introduction to AI and Cyber Security" are pivotal in preparing professionals to harness AI for robust cyber defense
Value Proposition
AI+ Cybersecurity empowers professionals with essential skills to protect against evolving cyber threats. By merging AI principles with cybersecurity practices, participants gain practical expertise in Python programming, machine learning, and advanced AI algorithms. Stay ahead in today's digital landscape with our hands-on training and drive innovation within your organization.
Additional Features
Alongside comprehensive AI and cybersecurity training, AI+ Cybersecurity offers interactive labs, expert-led discussions, and career development resources for professional growth within the cybersecurity field. Ongoing support from instructors and access to the latest tools ensure participants stay updated and equipped to address evolving cyber threats while driving innovation.