The RHCSA Rapid Track Course is designed for experienced Linux® system administrators who want to expand their technical skill sets and become accredited with the Red Hat® Certified System Administration (RHCSA) certification. To successfully navigate this course, students should have experience with the Linux command line—including the necessary skills to execute common commands, such as cp, grep, sort, mkdir, tar, mkfs, ssh, and dnf—and be familiar with accessing man pages for help. At the completion of the course, students will be adequately prepared to take the RHCSA exam (EX200) .
Date/Locations:
No Events
Duration: 5 days
Course Objectives:
Introduce Linux and the Red Hat Enterprise Linux ecosystem.
Run commands and view shell environments.
Manage, organize, and secure files.
Manage users, groups and user security policies.
Control and monitor systemd services.
Configure remote access using the web console and SSH.
Configure network interfaces and settings.
Manage software using DNF
Access security files, file systems, and networks
Execute shell scripting and automation techniques
Manage storage devices, logical volumes, and file systems
This course provides security professionals with the skills and knowledge to perform vulnerability and compliance scanning of supported operating systems, devices, and applications. Students will construct custom scan policies for topology discovery, network vulnerability detection, credentialed patch audits, and compliance benchmarks, and discuss the underlying technologies utilized by the Nessus scanner.
This course provides students with the necessary information to prepare for the Tenable Certified Nessus Auditor (TCNA) exam.
Date/Locations:
No Events
Duration: 5 days
Course Objectives:
Introduction to Nessus and Vulnerability Scanning
Nessus Installation and Administration
Basic Nessus Scan Operation
Nessus Scan Configuration and Policy Creation
Vulnerability Analysis and Reporting with Nessus
Advanced Scan Configuration and Policy Creation
Introduction to Compliance and Auditing
Nessus Auditing Features
Windows System Auditing
Unix System Auditing
Cisco IOS Auditing
Nessus Database Auditing
Nessus Content Auditing
Auditing to Industry Guidelines
Auditing to Federal Guidelines
Prerequisites:
Students should possess a basic understanding of TCP/IP networking, operating systems security, and common client/server applications.
CompTIA SecAI+ is the first certification in CompTIA’s expansion series, designed to help you secure, govern and responsibly integrate artificial intelligence into your cybersecurity operations. You’ll build the skills to defend AI systems, meet global compliance expectations and use AI to enhance threat detection, automation and innovation—so you can strengthen your expertise and help keep your organization’s systems and data secure.
SecAI+ helps you build practical AI security and automation skills on top of your existing expertise, so you can secure AI deployments, use AI‑assisted security tools with confidence, and stay ready for the next step in your cybersecurity career.
Course Objectives:
Apply AI concepts to strengthen your organization’s cybersecurity posture
Secure AI systems using advanced controls and protections to safeguard data, models, and infrastructure
Leverage AI technologies to automate workflows, accelerate incident response, and scale security operations
Navigate global GRC frameworks to ensure ethical and compliant AI adoption across industries
Defend against AI-driven threats like adversarial attacks, automated malware, and malicious use of generative AI
Integrate AI securely into DevSecOps pipelines and enterprise security strategies.
Dates/Locations:
No Events
Prerequisites: Recommended experience: 3–4 years in IT and 2+ years hands-on cybersecurity; Security+, CySA+, PenTest+, or equivalent recommended
SecAI+ (V1) exam objectives summary
Basic AI concepts related to cybersecurity (17%)
Explain core AI principles and terminology: Machine learning, deep learning, natural language processing, and automation.
Identify AI applications in security: Use cases for AI in threat detection, defense, and security operations.
Recognize AI-driven threats: Automated phishing, polymorphic malware, adversarial machine learning, and malicious use of generative AI.
Securing AI systems (40%)
Implement security controls: Protect AI systems, data, and models using robust technical safeguards.
Secure AI deployment environments: Apply best practices across on-premises, cloud, and hybrid infrastructures.
Mitigate adversarial risks: Defend against attacks targeting AI models, data pipelines, and inference layers.
AI-assisted security (24%)
Enhance detection and response: Use AI-driven tools to identify anomalies, detect threats, and accelerate incident remediation.
Automate security workflows: Integrate AI for event triage, alert correlation, and response orchestration.
Apply AI techniques in operations: Incorporate AI into threat modeling, behavior analysis, and continuous monitoring.
AI governance, risk, and compliance (19%)
Understand regulatory frameworks: Identify global governance requirements and their implications for AI adoption.
Integrate GRC into AI projects: Incorporate governance, risk management, and compliance practices throughout the AI lifecycle.
Ensure responsible AI use: Apply ethical guidelines, legal standards, and industry frameworks such as GDPR and NIST AI RMF.
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