Programme Parameters
Graduate / Intermediate
4 Weeks (40 Hrs)
Online (e-LMS)
• A basic understanding of the subject area and fundamental programming or scientific concepts.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
Cybersecurity and AI examines a relationship that runs in both directions. On one side, machine learning strengthens defence — detecting intrusions, malware and fraud faster than rules alone. On the other, attackers now wield AI to scale phishing and evade detection, and AI systems themselves become targets through poisoning and adversarial inputs. You study both, building defensive models and learning to reason about the new risks AI introduces. The course gives security-minded professionals a clear, practical map of where these two fields intersect and how to act on it. A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
This course examines the two-way relationship between AI and cybersecurity: using AI to defend systems, and defending against AI-enabled and AI-targeting attacks.
📋 Course Objectives
1. Apply machine learning to intrusion and malware detection.
2. Understand AI-enabled attacks such as automated phishing.
3. Explain adversarial and data-poisoning threats to ML.
4. Balance detection performance against false alarms.
5. Build a defensive posture for AI-enabled environments.
👥 Who Should Enroll?
• Security analysts and engineers
• Data scientists working in security
• IT professionals upskilling in AI
• Students specialising in cyber defence
🚀 Key Learning Outcomes
• A clear map of the AI–cybersecurity intersection.
• The ability to build a defensive detection model.
• Awareness of AI-specific threats and defences.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
💎 What You'll Gain
Live & Recorded Sessions
Lifetime access to class recordingse-Certificate on Completion
Cryptographically verified credentialPost-Programme Support
Direct access to mentors & councilHands-On Experience
Notebooks, real-world code & datasetsCurriculum Outline
AI Fundamentals, Mathematics, and Cybersecurity And Ai Foundations
Implement Artificial Intelligence with Cybersecurity for practical ai fundamentals, mathematics, and cybersecurity and ai foundations applications and outcomes. • Design Artificial Intelligence with Cybersecurity for practical ai fundamentals, mathematics, and cybersecurity and ai foundations applications and outcomes. • Analyze Artificial Intelligence with Cybersecurity for practical ai fundamentals, mathematics, and cybersecurity and ai foundations applications and outcomes.
Data Engineering, Preprocessing, and Feature Pipelines
Implement Artificial Intelligence with Cybersecurity for practical data engineering, preprocessing, and feature pipelines applications and outcomes. • Design Artificial Intelligence with Cybersecurity for practical data engineering, preprocessing, and feature pipelines applications and outcomes. • Analyze Artificial Intelligence with Cybersecurity for practical data engineering, preprocessing, and feature pipelines applications and outcomes.
Model Architecture, Algorithm Design, and Cybersecurity And Ai Methods
Implement Artificial Intelligence with Cybersecurity for practical model architecture, algorithm design, and cybersecurity and ai methods applications and outcomes. • Design Artificial Intelligence with Cybersecurity for practical model architecture, algorithm design, and cybersecurity and ai methods applications and outcomes. • Analyze Artificial Intelligence with Cybersecurity for practical model architecture, algorithm design, and cybersecurity and ai methods applications and outcomes.
Training, Hyperparameter Optimization, and Evaluation
Implement Artificial Intelligence with Cybersecurity for practical training, hyperparameter optimization, and evaluation applications and outcomes. • Design Artificial Intelligence with Cybersecurity for practical training, hyperparameter optimization, and evaluation applications and outcomes. • Analyze Artificial Intelligence with Cybersecurity for practical training, hyperparameter optimization, and evaluation applications and outcomes.
Deployment, MLOps, and Production Workflows
Implement Artificial Intelligence with Cybersecurity for practical deployment, mlops, and production workflows applications and outcomes. • Design Artificial Intelligence with Cybersecurity for practical deployment, mlops, and production workflows applications and outcomes. • Analyze Artificial Intelligence with Cybersecurity for practical deployment, mlops, and production workflows applications and outcomes.
Ethics, Bias Mitigation, and Responsible AI Practices
Implement Artificial Intelligence with Cybersecurity for practical ethics, bias mitigation, and responsible ai practices applications and outcomes. • Design Artificial Intelligence with Cybersecurity for practical ethics, bias mitigation, and responsible ai practices applications and outcomes. • Analyze Artificial Intelligence with Cybersecurity for practical ethics, bias mitigation, and responsible ai practices applications and outcomes.
Industry Integration, Business Applications, and Case Studies
Implement Artificial Intelligence with Cybersecurity for practical industry integration, business applications, and case studies applications and outcomes. • Design Artificial Intelligence with Cybersecurity for practical industry integration, business applications, and case studies applications and outcomes. • Analyze Artificial Intelligence with Cybersecurity for practical industry integration, business applications, and case studies applications and outcomes.
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Artificial Intelligence |
| Covered Tool / Platform | Cybersecurity |
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