Ementorhub

What you'll learn

Implement AI-driven techniques for detecting and mitigating advanced malware and network anomalies effectively.

Utilize Generative Adversarial Networks (GANs) to understand and counteract adversarial attacks in AI systems.

Evaluate AI model performance and apply reinforcement learning to enhance adaptive cybersecurity measures.

Skills you'll gain

Network Analysis

Feature Engineering

Threat Detection

Authentications

Anomaly Detection

Deep Learning

Network Security

Intrusion Detection and Prevention

Generative AI

Artificial Intelligence and Machine Learning (AI/ML)

Email Security

Cybersecurity

Specialization - 3 course series

In the "AI for Cybersecurity" specialization, learners will apply AI techniques to develop practical cybersecurity tools. They will create both machine learning (ML) and deep learning (DL) models to detect IoT botnet activity in network traffic, emphasizing feature engineering for ML and optimizing raw data for DL. Additionally, participants will design a metamorphic malware detector using a Hidden Markov Model, analyzing opcode sequences to classify them as malware or legitimate software. Throughout these projects, learners will export models, test them on unseen data, and submit video demonstrations along with their code. This hands-on approach equips learners with skills in AI-driven threat detection and model implementation for real-world cybersecurity challenges.

Advanced Malware and Network Anomaly Detection

Securing AI and Advanced Topics