SecAI+: AI-Powered Cybersecurity Certification Training
Learn how to secure AI systems, detect AI-driven cyber threats, and integrate artificial intelligence into modern security operations while preparing for the Se...
Learn how to secure AI systems, detect AI-driven cyber threats, and integrate artificial intelligence into modern security operations while preparing for the Se...
SecAI+: AI-Powered Cybersecurity Certification Training prepares cybersecurity professionals to secure artificial intelligence systems and use AI technologies to strengthen modern security operations. This course aligns with the latest SecAI+ (CY0-001) certification objectives and teaches learners how AI intersects with cybersecurity, including threat detection, automated response, AI governance, and secure deployment of machine learning systems.
As organizations increasingly adopt AI technologies, cybersecurity teams must understand how to defend AI models, data pipelines, and infrastructure from emerging threats such as adversarial attacks, automated malware, and AI-driven phishing campaigns. This training provides hands-on knowledge of AI security architecture, risk management, and governance frameworks.
Learners will explore how AI can enhance security operations by automating workflows, accelerating incident response, and improving threat intelligence analysis. The course also covers responsible AI adoption, compliance standards, and ethical considerations for AI deployment in enterprise environments.
By completing this training, participants gain the knowledge and skills needed to secure AI systems across cloud, hybrid, and on-premises environments while preparing for the SecAI+ certification exam and future roles in AI-driven cybersecurity.
- Introduction
- Lesson 1.1: Explain AI Concepts for Cybersecurity
- Core AI Types
- Types of AI
- Generative AI
- Generative AI
- Machine Learning and Statistical Learning
- Detect Suspicious Activity using ML
- Transformers
- Deep Learning
- Lesson 1.2 Understand AI Model Training and Prompt Engineering
- AI Model Training
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
- Federated Learning
- Model Training Techniques
- Introduction to Prompt Engineering
- System Roles and System Prompts
- System Roles and Prompts
- User Prompts
- Zero-Shot, One-Shot, Multi-Shot, and Templates
- Securing the Model
- Lesson 1.3 Secure AI Data
- Data Security Related to AI
- Data Security Considerations for AI
Basic understanding of cybersecurity concepts and IT systems
Familiarity with networking, operating systems, and security fundamentals
Recommended certification such as Security+ or equivalent knowledge
Approximately 2+ years of cybersecurity experience is helpful but not mandatory
Interest in AI, machine learning, and modern security operations
Understand core AI and machine learning concepts relevant to cybersecurity
Identify and mitigate threats targeting AI systems and machine learning models
Implement security controls to protect AI data, models, and infrastructure
Use AI-powered tools to improve threat detection and incident response
Apply governance, risk, and compliance frameworks to responsible AI deployment
Secure AI systems across cloud, hybrid, and on-premises environments
Prepare for the SecAI+ (CY0-001) certification exam
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Last Updated
Mar 14, 2026
Students
99+
language
English
Duration
10h++Level
beginner
Expiry period
Lifetime
Certificate
Yes
bigoss
English
Certificate Course
99+ Students
10h++
43 Courses
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