Study smarter for cybersecurity & AI certifications

Entry-level security fundamentals — threats, cryptography, identity, network security, and risk.

Analyst-tier blue-team skills — SOC workflows, threat intelligence, incident response, and SIEM.

Hands-on red-team — scoping, scanning, exploitation, reporting, and post-exploitation.

Advanced architecture & engineering — enterprise security, cryptography, and research. Renamed from CASP+ in Dec 2024.

Network infrastructure fundamentals — OSI, routing, switching, wireless, and network security basics.

Linux administration and security — system management, scripting, containers, and troubleshooting.

Cloud infrastructure — deploying, securing, and maintaining hybrid cloud environments.

IT project management fundamentals — lifecycle, constraints, communication, and stakeholder management.

Ethical hacking methodology across footprinting, scanning, system hacking, and malware.

Digital forensics — evidence acquisition, analysis, incident handling, and reporting.

Executive security leadership — governance, risk, finance, and security program management.

Network defense operations — perimeter, IDS/IPS, endpoint protection, and threat analysis.

Incident handling and response — preparation, containment, eradication, and recovery.

IT audit and assurance — auditing, governance, acquisition, and operations.

Security management and leadership — governance, risk, program development, and incident response.

Enterprise IT risk management — identification, assessment, response, and control monitoring.

Enterprise IT governance — framework, strategic alignment, value delivery, and risk optimization.

Entry-level cybersecurity fundamentals — concepts, network security, and operations basics.

Hands-on practitioner security — access controls, network security, cryptography, and operations.

Senior security management — the eight domains spanning governance, risk, architecture, and operations.

Cloud security architecture — securing AWS/Azure/GCP workloads, data, IAM, and operations.

Secure software development lifecycle — requirements, design, coding, testing, and deployment.

Healthcare security & privacy — HIPAA, medical data protection, and compliance.

CISSP concentration — security architecture, design, and enterprise solutions.

CISSP concentration — security engineering, systems development, and certification/accreditation.

CISSP concentration — security management, leadership, and enterprise governance.

Foundational Microsoft security, compliance, and identity concepts across M365 and Azure.

Microsoft Entra ID administration — authentication, conditional access, governance, and PIM.

Threat detection and response using Microsoft Sentinel and Defender XDR.

Expert-level Zero Trust security architecture across identity, cloud, data, and endpoints.

Information protection & compliance — Purview, DLP, data lifecycle, and insider risk.

Securing Azure workloads — Defender for Cloud, Key Vault, network security, and data protection.

Cloud fundamentals — Azure services, pricing, SLAs, and core cloud concepts.

Securing AWS workloads — IAM, network, data protection, incident response, and logging.

Foundational AWS cloud concepts — services, security, pricing, and architecture basics.

Designing resilient, secure AWS architectures — compute, storage, networking, and well-architected.

Securing Google Cloud — IAM, VPC controls, Security Command Center, and data protection.

Foundational cloud & AI knowledge — Google Cloud value, services, security, and innovation.

Foundational AI literacy — concepts, use cases, responsible AI, and business impact.

Professional AI fundamentals — data, models, deployment, and operationalizing AI solutions.

AI fundamentals on Azure — ML, computer vision, NLP, and responsible AI principles.

Building and deploying Azure AI solutions — cognitive services, NLP, and generative AI integration.

Designing and running ML experiments on Azure — Azure ML, model training & deployment.

Operationalizing ML and generative AI solutions — deployment, governance, monitoring, and optimization.

Architecting AWS ML pipelines — SageMaker, data engineering, model deployment, and MLOps.

Foundational AI/ML on AWS — concepts, use cases, AWS AI services, and responsible AI.

Designing Vertex AI ML systems — pipelines, Vertex AI, model evaluation, and responsible AI.

Generative AI strategy on Google Cloud — Gemini, Vertex AI, use cases, and responsible AI.