Certified Cyber & AI Security Fundamentals (CCAIS-F) Certification Program by Tonex
This certification program builds a practical bridge between core cybersecurity fundamentals and rapidly evolving AI technologies. Participants learn how digital systems, data, and models can be exposed when AI capabilities are deployed without structured security thinking. The program explains where classical controls still work and where AI introduces new weaknesses and attack paths. Emphasis is placed on real environments such as cloud platforms, enterprise applications, and connected devices. Several sections focus on cybersecurity impact so participants can see how AI driven threats change risk profiles, monitoring needs, and response expectations. By the end, participants will be able to speak confidently with technical and business stakeholders about AI security strategy and realistic protection measures.
Learning Objectives
- Understand the foundational concepts of cyber risk, AI principles, and their combined influence on modern systems
- Identify common threat categories affecting data, models, identities, and infrastructure in AI enabled environments
- Map security controls to AI lifecycle stages from data collection through deployment and ongoing operations
- Relate business requirements, governance expectations, and compliance demands to concrete security decisions in AI projects
- Explain how cybersecurity practices must adapt to adversarial AI, model abuse, and automated attack techniques
- Evaluate the cybersecurity impact of AI adoption across critical services and prioritize investments accordingly
Audience
- Cybersecurity Professionals
- Security architects and security engineers
- AI and machine learning engineers
- IT and cloud infrastructure administrators
- Risk, audit, and compliance specialists
- Technical project and product managers
- Technology leaders and decision makers
Program Modules
Module 1: Cyber and AI Security Foundations
- Core security and AI concepts
- Digital assets and attack surfaces
- AI components within system architectures
- Confidentiality, integrity, availability focus
- Risk categories for AI systems
- Roles and responsibilities in security
Module 2: Threat Modeling in Intelligent Systems
- Identifying assets and trust boundaries
- Enumerating AI specific threat scenarios
- Data poisoning and model manipulation paths
- Abuse of AI powered functionalities
- Prioritizing threats with simple scoring
- Documenting and updating threat models
Module 3: Secure Data, Models, and Pipelines
- Data classification and minimization practices
- Secure data ingestion and preprocessing steps
- Protecting training datasets at rest
- Hardening model artifacts and repositories
- Securing MLOps and deployment pipelines
- Monitoring data and model drift
Module 4: Defensive Controls for AI Workloads
- Identity and access controls for AI services
- Network protections around AI components
- Logging and telemetry for AI activities
- Detection patterns for AI specific abuse
- Response playbooks for AI related incidents
- Integrating controls with existing platforms
Module 5: Governance, Compliance, and Ethical AI
- Policy frameworks for AI security
- Regulatory expectations on data and AI use
- Documentation for audits and oversight needs
- Third party and vendor risk considerations
- Transparency, explainability, and accountability
- Alignment with organizational risk appetite
Module 6: Capstone Integration and Exam Readiness
- Reviewing key cyber and AI concepts
- Linking threats, controls, and governance
- Interpreting scenarios and choosing responses
- Common misconceptions and error patterns
- Preparation strategies for the certification exam
- Personal roadmap for ongoing skill growth
Exam Domains
- Cybersecurity and AI Fundamentals
- AI Threats, Vulnerabilities, and Attack Surfaces
- Secure Data, Model, and Pipeline Protection
- AI Security Operations and Incident Handling
- Governance, Risk, Compliance, and Ethical AI
- Integrated Cyber and AI Security Strategy
Course Delivery
The course is delivered through a combination of lectures, interactive discussions, guided exercises, and case based reviews, facilitated by experts in cyber and AI security. Participants have access to online resources such as readings, structured examples, templates, and curated tools that support practical understanding. The delivery approach supports both technical and semi technical roles, ensuring that everyone can connect concepts to their own environment and responsibilities.
Assessment and Certification
Participants are assessed through quizzes, structured assignments, and a final examination that validates understanding of cyber and AI security fundamentals. Performance is measured on both conceptual knowledge and the ability to apply ideas in realistic scenarios. Upon successful completion of the program requirements, participants receive the Certified Cyber & AI Security Fundamentals (CCAIS-F) Certification from Tonex.
Question Types
- Multiple Choice Questions (MCQs)
- Scenario-based Questions
Passing Criteria
To pass the Certified Cyber & AI Security Fundamentals (CCAIS-F) Certification Program exam, candidates must achieve a score of 70% or higher.
Strengthen your foundation at the intersection of cybersecurity and AI before attackers and compliance pressures force rushed decisions. Enroll in the Certified Cyber & AI Security Fundamentals (CCAIS-F) Certification Program by Tonex to build practical, defensible skills that you can apply immediately in your organization.