Artificial Intelligence and Machine Learning Courses

AI+ Security Level 3 - Self-paced

Length 365 days access
Price NZD 1050 exc GST
Inclusions Online exam

Course overview

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Why study this course

The AI+ Security Level 3 course provides a comprehensive exploration of the intersection between AI and cybersecurity, focusing on advanced topics critical to modern security engineering. It covers concepts in AI and machine learning for security, delving into areas like threat detection, response mechanisms, and the use of deep learning for security applications. The course addresses the challenges of adversarial AI, network and endpoint security, and secure AI system engineering, along with emerging topics such as AI for cloud, container security, and blockchain integration. Key subjects also include AI in identity and access management (IAM), IoT security, and physical security systems, culminating in a hands-on capstone project that tasks learners with designing and engineering AI-driven security solutions.

Exam and certification

This course prepares students for the corresponding certification. The exam/assessment is completed online and provided as part of the course content.

The exam is:

90 minutes
50 multiple choice / multiple response questions
Pass mark is 35 out of 50 (i.e. 70%)
Online via AI Proctoring platform

This course offers a combination of online labs, projects, and case studies.

Course availability update

Lumify Work is actively monitoring demand for this course. It is currently offered as a self-paced eLearning course and includes the certification exam. If you're interested in joining a waitlist for future instructor-led training — or exploring options for a tailored delivery for your organisation — please contact us. Your feedback helps shape our activation roadmap.

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What you’ll learn

This course is designed to teach participants how to:

Use deep learning algorithms for advanced applications like malware analysis, phishing detection, and predictive threat modelling
Apply AI techniques to streamline identity verification, manage access control systems, and secure authentication processes
Understand the use of AI for securing cloud-based platforms and containerised applications, focusing on scalability and automation in threat mitigation
Explore how AI can be used to address unique IoT security challenges, including detecting compromised devices and protecting communication protocols

AI CERTs at Lumify Work

AI CERTs™ stands at the forefront of AI and blockchain certification, offering world-class programs that prepare individuals to lead in these rapidly growing fields. AI CERTs courses and certifications are vendor agnostic and designed to bridge the gap between theoretical knowledge and practical application, ensuring learners are equipped to make an immediate impact in their careers.
Lumify Work is a Platinum Authorized Training Partner for AI CERTs in Australia, New Zealand, and the Philippines.

View all AI CERTs at Lumify Work courses

Who is the course for?

This course is intended for:

Cybersecurity Professionals
Risk Management Specialists
Compliance Officers
IT Security Analysts
Ethical Hackers and Penetration Testers
Tech-Savvy Leaders
Aspiring AI Security Experts

Course subjects

Module 1: Foundations of AI and Machine Learning for Security Engineering

Core AI and ML Concepts for Security
AI Use Cases in Cybersecurity
Engineering AI Pipelines for Security
Challenges in Applying AI to Security

Module 2: Machine Learning for Threat Detection and Response

Engineering Feature Extraction for Cybersecurity Datasets
Supervised Learning for Threat Classification
Unsupervised Learning for Anomaly Detection
Engineering Real-Time Threat Detection Systems

Module 3: Deep Learning for Security Applications

Convolutional Neural Networks (CNNs) for Threat Detection
Recurrent Neural Networks (RNNs) and LSTMs for Security
Autoencoders for Anomaly Detection
Adversarial Deep Learning in Security

Module 4: Adversarial AI in Security

Introduction to Adversarial AI Attacks
Defense Mechanisms Against Adversarial Attacks
Adversarial Testing and Red Teaming for AI Systems
Engineering Robust AI Systems Against Adversarial AI

Module 5: AI in Network Security

AI-Powered Intrusion Detection Systems
AI for Distributed Denial of Service (DDoS) Detection
AI-Based Network Anomaly Detection
Engineering Secure Network Architectures with AI

Module 6: AI in Endpoint Security

AI for Malware Detection and Classification
AI for Endpoint Detection and Response (EDR)
AI-Driven Threat Hunting
Implementing Lightweight AI Models for Resource-Constrained Devices

Module 7: Secure AI System Engineering

Designing Secure AI Architectures
Cryptography in AI for Security
Ensuring Model Explainability and Transparency in Security
Performance Optimisation of AI Security Systems

Module 8: AI for Cloud and Container Security

AI for Securing Cloud Environments
AI-Driven Container Security
AI for Securing Serverless Architectures
AI and DevSecOps

Module 9: AI and Blockchain for Security

Fundamentals of Blockchain and AI Integration
AI for Fraud Detection in Blockchain
Smart Contracts and AI Security
AI-Enhanced Consensus Algorithms

Module 10: AI in Identity and Access Management (IAM)

AI for User Behaviour Analytics in IAM
AI for Multi-Factor Authentication (MFA)
AI for Zero-Trust Architecture
AI for Role-Based Access Control (RBAC)

Module 11: AI for Physical and IoT Security

AI for Securing Smart Cities
AI for Industrial IoT Security
AI for Autonomous Vehicle Security
AI for Securing Smart Homes and Consumer IoT

Module 12: Capstone Project - Engineering AI Security Systems

Defining the Capstone Project Problem
Engineering the AI Solution
Deploying and Monitoring the AI System
Final Capstone Presentation and Evaluation

Prerequisites

Completion of AI+ Security Level 2 is mandatory
Intermediate/Advanced Python Programming: Proficiency or expert in Python, including deep learning works (TensorFlow, PyTorch)
Intermediate Machine Learning Knowledge: Proficiency in understanding of deep learning, adversarial AI, and model training
Advanced Cybersecurity Knowledge: Proficiency in threat detection, incident response, and network/endpoint security
AI in Security Engineering: Knowledge of AI’s role in identity and access management (IAM), IoT security, and physical security
Cloud and Container Expertise: Understanding of cloud security, containerisation, and blockchain technologies
Linux/CLI Mastery: Advanced command-line skills and experience with security tools in Linux environments

Terms & Conditions

The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.