Gain the knowledge and skills needed to implement security controls, maintain the security posture, and identify and remediate vulnerabilities by using a variety of security tools. The course covers scripting and automation, virtualization, and cloud N-tier architecture.
After completing this course, students will be able to describe specialized data classifications on Azure, Identify Azure data protection mechanisms, Implement Azure data encryption methods, Secure internet protocols and how to implement them on Azure, Describe Azure security services and features.
TechNow has worked worldwide enterprise infrastructures for over 20 years and has developed demos and labs to exemplify the techniques required to demonstrate cloud technologies and to effectively manage security in the cloud environment.
Attendees to AZ-500: Microsoft Azure Security Technologies will receive TechNow approved course materials and expert instruction.
Date/Locations:
No Events
Course Duration: 5 days
Course Outline:
Identity and access
Configure Azure Active Directory for Azure workloads and subscriptions
Configure Azure AD Privileged Identity Management
Configure security for an Azure subscription
Platform Protection
Understand cloud security
Build a network
Secure network
Implement host security
Implement platform security
Implement subscription security
Security Operations
Configure security services
Configure security policies by using Azure Security Center
Looking to move up in the information security field? If you have at least one year of security experience, you qualify for the Systems Security Certified Practitioner (SSCP) certification, which offers junior security professionals a way to validate their experience and demonstrate competence with (ISC²)®’s seven domains.
Attendees to TN-715: Systems Security Certified Practitioner (SSCP) will receive TechNow approved course materials and expert instruction.
Instructor comments: Instructor was very knowledgeable on most items covered during this course. There were some topics he did lack the answer to. Instructor would also get sidetracked easily
User: keginth
Instructor comments: he was phenomenal with test prep and knew the book well
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.
