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.
- Certification Duration: 40 hours (5 Days)
Why This Certification Matters
- Comprehensive AI-Cybersecurity Integration:Understand how AI and Cybersecurity merge, enhancing your capability to combat evolving digital threats effectively.
- Advanced Threat Detection TechniquesMaster ML techniques to identify and mitigate email threats, malware, and network anomalies, improving cybersecurity defense.
- Real-World Application FocusApply 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.
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.
Exam Policies & Integrity
- Before your exam, you must accept the AI CERTs™ Candidate Agreement. It ensures fairness, transparency, and unbiased certification for all candidates.
- Please review it in advance to understand our exam standards and your responsibilities.
Available Dates
Exam Details
Modules
10
Examination
1
50 MCQs
90 Minutes
Passing Score
70%
Recertification Requirements
- AI CERTs requires recertification every year to keep your certification valid. Notifications will be sent three months before the due date, and candidates must follow the steps in the candidate handbook to complete the process.
- Need Help? If you have any questions or need assistance with recertification, please reach out to our support team at support@aicerts.ai
Certification Modules
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
Tools
CrowdStrike
Microsoft Cognitive Toolkit (CNTK)
Flair.ai
Exam Objectives
- 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.
Career Opportunities Post-Certification
- Median Salaries : $90,000
- With AI Skills : $1,15,000
- % Difference : 28
AI Security Career Advancement – Your Path to Cyber Resilience
- Market Demand for AI Security Experts
- With AI-driven cyberattacks on the rise, organisations demand advanced AI security experts who can defend against evolving threats.
- Studies indicate that 82% of enterprises prioritise AI security as part of their risk management strategies.
- High-Growth Areas: Adversarial AI Defence, AI Risk Management, AI-Powered Threat Detection, and Secure AI Governance.
- AI security expertise is in high demand across financial institutions, government agencies, healthcare, and global tech firms, making it a lucrative career move.
Smart Solutions for AI- Powered Credentials
- Secure, tamper-proof certifications with blockchain technology and Al integration. Instant verification and custom designs for your brand.
- Al-enhanced proctoring for reliable assessments with automated integrity checks and live monitoring. Powering the future of certifications with Al and blockchain.
Trusted LinkedIn Reviews Posted by Our Learners
Santosh Singh
Senior IT Infrastructure Manager at NETCOM LEARNING INDIA PRIVATE LIMITED.
I am officially AI+ Security™ Certified! Equipped to lead in the era of innovation and technology!
Sandeep Sisodiya
Platform Engineering | SRE | DevOps | AI Security | Automation | Cloud
Excited to share that I have earned my AI+ Security™: Level 2 certification from AI CERTs™. This program deepened my understanding of the integration of Artificial Intelligence/Machine Learning and Cybersecurity. A huge thank you to Abhishar Balodhi and the amazing team at NetCom Learning for their guidance and insights! Looking forward to applying these skills in real-world projects. If you are also exploring AI, lets connect and exchange insights!
Rammohan Thirupasur
Freelance Sr. Trainer - Coach - Advisor | Gen AI Security - ICS/OT Security - AI GRC - DORA - Sovereign AI - Oracle Cloud Infrastructure (OCI) - AI Product Management - Design Thinking - Leadership - Keynote Speaker
"""𝗜𝗻 𝗮𝗻 𝗲𝗿𝗮 𝘄𝗵𝗲𝗿𝗲 𝘁𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 𝗲𝘃𝗼𝗹𝘃𝗲𝘀 𝗮𝘁 𝗹𝗶𝗴𝗵𝘁𝗻𝗶𝗻𝗴 𝘀𝗽𝗲𝗲𝗱, 𝘄𝗲 𝗺𝘂𝘀𝘁 𝗽𝗿𝗶𝗼𝗿𝗶𝘁𝗶𝘇𝗲 𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆. 𝗔𝘀 𝘄𝗲 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗲 𝗔𝗜 𝗶𝗻𝘁𝗼 𝗲𝘃𝗲𝗿𝘆 𝗳𝗮𝗰𝗲𝘁 𝗼𝗳 𝗼𝘂𝗿 𝗹𝗶𝘃𝗲𝘀,𝘁𝗵𝗲 𝗿𝗶𝘀𝗸𝘀 𝗮𝘀𝘀𝗼𝗰𝗶𝗮𝘁𝗲𝗱 𝘄𝗶𝘁𝗵 𝗶𝘁𝘀 𝗺𝗶𝘀𝘂𝘀𝗲 𝗲𝘀𝗰𝗮𝗹𝗮𝘁𝗲. 𝗪𝗲 𝗰𝗮𝗻𝗻𝗼𝘁 𝗮𝗳𝗳𝗼𝗿𝗱 𝘁𝗼 𝗯𝗲 𝗰𝗼𝗺𝗽𝗹𝗮𝗰𝗲𝗻𝘁"" - Dr. Fei-Fei As a Senior Leader & Instructor specializing in AI Security, I firmly believe that my role extends beyond training & evangelizing...it’s about anticipating the future of technology and preparing the young security minds in the industry for the challenges ahead. On this wintry Sunday afternoon, I pursued the 𝗔𝗜 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗜𝗻𝘀𝘁𝗿𝘂𝗰𝘁𝗼𝗿 𝗰𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 & aced it with 100% . While the path to this certification was steep, I’m proud to share that I have cracked it. Look , It's important for me to be 4 steps ahead. I regularly apply the knowledge gained from certifications in real-world scenarios. This hands-on approach not only enhances my skills but also enriches the learning experience for participants of my workshops or boot camps. As we navigate the complexities of AI security, I’m excited to share my insights and experiences. I deliver niche & bespoke training in a 𝗱𝗮𝘁𝗮-𝗱𝗿𝗶𝘃𝗲𝗻 𝘀𝘁𝗼𝗿𝘆 𝘁𝗲𝗹𝗹𝗶𝗻𝗴 𝗳𝗼𝗿𝗺𝗮𝘁 𝘂𝘀𝗶𝗻𝗴 𝗗𝗲𝘀𝗶𝗴𝗻 𝗧𝗵𝗶𝗻𝗸𝗶𝗻𝗴 𝗺𝗲𝘁𝗵𝗼𝗱𝗼𝗹𝗼𝗴𝘆. With 24 yrs of I.T experience including 17 yrs in Leadership role , I am uniquely placed to help you succeed. 𝗗𝗠 𝗺𝗲 . 𝗜 𝗮𝗺 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗯𝗲𝘀𝘁 𝗶𝗻 𝘁𝗵𝗲 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀. 𝗜 𝗮𝗺 𝗳𝗼𝗿𝗴𝗲𝗱 𝘁𝗵𝗮𝘁 𝘄𝗮𝘆 !! Together, let's build a secure future in AI technology."
Discover Your Ideal Role-Based Certifications and Programs!
Not sure which certifications to go for? Take our quick assessment to discover the perfect role-based certifications and programs tailored just for you.
Frequently Asked Questions
Is any prior programming experience required for this course?
- No prior programming experience is necessary. The course begins with fundamental Python programming tailored for AI and Cybersecurity applications, making it suitable for beginners.
How will this course help me in my professional career?
- This course equips professionals with cutting-edge knowledge and practical skills in integrating AI with Cybersecurity, enhancing their ability to protect digital assets and address modern cyber threats effectively.
What is the focus of the Capstone Project in this course?
- The Capstone Project focuses on synthesizing the skills learned throughout the course to address real-world cybersecurity challenges, enabling participants to leverage AI effectively to safeguard digital assets.
How do I enroll in the course?
- Visit the official website, complete the registration process, and access the course materials immediately after payment.
How is the course structured?
- The course is structured into ten modules, each focusing on different aspects of AI and cybersecurity, from fundamental concepts to advanced applications, culminating in a Capstone Project.
