Ethical Hacking and AI Security
Ethical Hacking and AI Security is a intermediate-level, 3 Weeks online course by NSTC. Master key concepts and practical skills in Artificial Intelligence through hands-on projects, real-world case studies, and expert mentorship.
- ModeOnline (e-LMS)
- LevelIntermediate
- Duration3 Weeks
- Fee₹4,249
| Attribute | Detail |
|---|---|
| Format | Online (e-LMS) |
| Level | Intermediate |
| Duration | 3 Weeks |
| Certification | e-Certification + e-Marksheet |
| Fee | ₹4249 / $56 |
| Tools | Python TensorFlow PyTorch Keras Scikit-learn Jupyter Notebook Google Colab Hugging Face |
About the Ethical Hacking and AI Security Course
The program covers key concepts such as AI-driven vulnerability assessment, network security, and AI security risk mitigation.
It combines traditional ethical hacking techniques with AI-driven approaches to provide a comprehensive understanding of security in AI-driven environments.
Program Highlights
• Comprehensive coverage of Ethical Hacking and AI Security from fundamentals to advanced applications
• Hands-on projects and real-world case studies in Artificial Intelligence
• Expert-curated curriculum aligned with current industry standards
• Access to recorded lectures and e-LMS platform for flexible, self-paced learning
• e-Certification and e-Marksheet upon successful completion
• Dedicated mentor support and interactive doubt-clearing sessions
• Exposure to industry-standard tools and platforms used in Artificial Intelligence
• Career-oriented training for academic and professional growth in Artificial Intelligence
Course Curriculum
Module 1: Introduction to Ethical Hacking and AI Security
- Lesson 1.1: Introduction to Cybersecurity
- Lesson 1.2: Ethical Hacking: Principles and Practices
- Lesson 1.3: The Role of Ethical Hacking in Enhancing Security
- Lesson 1.4: Real-World Examples of Ethical Hacking in Cybersecurity
Module 2: Legal and Ethical Frameworks for Ethical Hacking
- Lesson 1.1: Understanding Cybersecurity Laws and Regulations
- Lesson 1.2: The Ethics of Hacking: Legal Boundaries and Responsibilities
- Lesson 1.3: Key Regulations Governing Ethical Hacking Globally
- Lesson 2.1: AI and Ethics: A Broad Overview
Module 3: AI-Driven Threat Detection
- Lesson 1.1: AI in Threat Detection: An Overview
- Lesson 1.2: Machine Learning Algorithms for Cyber Threat Detection
- Lesson 1.3: Advanced Threat Detection Using Deep Learning
- Lesson 1.4: Real-World AI-Driven Threat Detection Examples
Module 4: Penetration Testing with AI
- Lesson 1.1: Introduction to Pen Testing: Purpose and Scope
- Lesson 1.2: The Stages of a Pen Test: A Detailed Breakdown
- Lesson 1.3: Pen Testing Methodologies and Standards
- Lesson 2.1: The Role of AI in Automating Pen Testing
Module 5: Exploiting Vulnerabilities in AI Systems
- Lesson 1.1: Understanding AI Model Vulnerabilities
- Lesson 1.2: Adversarial Attacks: Techniques and Implications
- Lesson 1.3: Model Stealing Attacks: How They Work
- Lesson 1.4: Case Studies of Adversarial and Model Stealing Attacks
Module 6: AI for Phishing Detection and Prevention
- Lesson 1.1: Introduction to Phishing Detection
- Lesson 1.2: Machine Learning Techniques for Phishing Detection
- Lesson 1.3: AI-Based Tools for Anti-Phishing
- Lesson 2.1: Real-Time Threat Detection with AI
Module 7: Adversarial Machine Learning
- Lesson 1.1: Introduction to Adversarial Machine Learning
- Lesson 1.2: Evasion Attacks: How They Impact Models
- Lesson 1.3: Poisoning and Model Inversion Attacks Explained
- Lesson 2.1: Adversarial Training: Strengthening AI Models
