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Mimir, Keeper of the Well of Wisdom
CompTIA SecAI+ CY0-001: Full Certification Prep Bootcamp
https://www.udemy.com/course/comptia-secai-cy0-001-full-
certification-prep-bootcamp/
Year : 2026
Language : English
Level : All Levels
Category : IT & Software
Subcategory : IT Certifications
Duration : 11h 0m
Lectures : 99
Rating : 4.8/5 (25 reviews)
Students : 219
INSTRUCTOR(S)
HEADLINE
CY0-001 exam prep: AI threats, secure AI systems, SOC
automation & governance. Aligned to official CompTIA
objectives
WHAT YOU'LL LEARN
* 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.
REQUIREMENTS
* Basic knowlege of AI will be helpful
* Solid foundation in cyber security
WHO IS THIS COURSE FOR
* Cyber security professionals who want to acquire an AI
related
certification
* IT professionals looking to advance their career in
cybersecurity.
* Students pursuing a career in information security.
DESCRIPTION
AI is already inside your organisation's attack surface.
Security professionals who can't secure AI systems or use AI
to
strengthen their defences are going to be left behind. This
course prepares you to pass the CompTIA SecAI+ CY0-001 exam
and
walk into that gap with verified, vendor-neutral credentials.
What You'll Learn Map the full AI threat landscape using MITRE
ATLAS, OWASP LLM Top 10, and the MIT AI Risk Repository and
apply the right compensating controls per scenario Identify
and
defend against AI-specific attacks: prompt injection, model
poisoning, data poisoning, model inversion, membership
inference, and AI supply chain attacks Implement gateway
controls ? prompt firewalls, token limits, rate limiting, and
modality restrictions to lock down LLM-facing attack surfaces
Use AI-enabled tools (chatbots, CLI plug-ins, MCP servers) to
accelerate incident management, vulnerability analysis, and
automated penetration testing Apply the NIST AI Risk
Management
Framework, EU AI Act, ISO AI standards, and OECD guidelines to
real corporate AI deployment decisions Secure the full AI
model
lifecycle from data collection and preparation through
deployment, monitoring, and feedback loops Detect and audit
for
hallucinations, model bias, and AI cost anomalies across
production environments Leverage ChatGPT and Claude for
practical security tasks including vulnerability management
and
threat intelligence workflows Evaluate AI governance
structures
? AI Center of Excellence, shadow AI risk, sanctioned vs.
unsanctioned model policies ? and advise on compliant
deployment
Why This Course Built directly against the official CompTIA
SecAI+ CY0-001 exam objectives with every domain and sub-
objective 11 hours of video content structured to match the
four
exam domains: Basic AI Concepts (17%), Securing AI Systems
(40%), AI-assisted Security (24%), and AI GRC (19%) 200+
knowledge-check quizzes distributed throughout, plus a full
exam
simulation at the end that mirrors the real CY0-001 format
with
60 questions, 60 minutes, performance-based and multiple
choice
Every student gets a PDF summary book and the complete slide
deck so you're not hunting for notes when exam day arrives Who
This Is For SOC analysts and security engineers who work
alongside AI-integrated tools and need to understand the
attack
surface they're sitting in front of IT pros ? sysadmins,
network
engineers, helpdesk leads with 2+ years of hands-on experience
who want to formalise their move into security roles Security
professionals preparing specifically for the CompTIA SecAI+
CY0-001 V1 certification exam Not for you if you have zero IT
background becuase this exam assumes 3?4 years of IT
experience
and 2 years in cybersecurity; the course assumes the same.
What
You'll Walk Away With You'll pass the CY0-001 exam prepared
not
just familiar with the objectives, but able to reason through
performance-based questions on AI attack scenarios, control
implementation, and GRC decisions. You'll also have a working
vocabulary for AI security that holds up in interviews, in SOC
conversations, and when your organisation asks you to evaluate
an AI deployment. Bottom Line The SecAI+ is one of the first
vendor-neutral certifications that treats AI as a security
domain in its own right not a footnote. This course gives you
the structured preparation to pass it on the first attempt.
Enrol, work through it at your own pace, and come out the
other
side with a credential that means something.
COURSE CONTENT
Chapter 1: Introduction to the SECAI+ Exam
1. Welcome to the Course
2. The SECAI+ Exam - What you Need to Know
3. Download the Slides and Exam Objectives
Chapter 2: MODULE 1 - AI Concepts for Cybersecurity
4. Section Preview
5. Core AI Types in Cybersecurity
6. Types of AI
7. Generative AI
8. Machine Learning & Statistical Learning
9. Detecting Suspicious Activity using ML
10. Transformers
11. Deep Learning
12. Natural Language Processing
Chapter 3: AI Model Training & Prompt Engineering
13. Section Preview
14. AI Model Training
15. Supervised Learning
16. Unsupervised Learning
17. Reinforcement Learning
18. Federated Learning
19. Introduction to Prompt Engineering
20. User Prompts
21. Demo 1 - Using ChatGPT to Summarize Threat Reports
22. Demo 2 - Using ChatGPT for Vulnerability Identification
23. Zero-Shot, One-Shot, Multi-Shot & Templates
24. Securing the Model
Chapter 4: Secure AI Data
25. Section Preview
26. Data Security Related to AI
27. Data Security Considerations for AI
28. AI Data Types
29. Data Handling Techniques
Chapter 5: MODULE 2.0 - Implementing Threat Modeling and
Securing AI Systems
30. Section Preview
31. Introduction to AI Threat Modelling
32. Utilziing AI Threat Resources
33. Prerequisites for Performing AI Threat Modelling
34. Process of AI Threat Modelling
35. Threat Modelling Frameworks
Chapter 6: Implement Security Controls for AI Systems
36. Section Preview
37. Overview of AI Security Controls
38. Model Specific Controls
39. Model Guardrails
40. Prompt Template
41. Gateway & Interface Controls
42. Gateway Controls & Guardrails
43. Usage & Quota Limitations
44. Testing Security Controls
Chapter 7: MODULE 3.0 - Installing Access Controls for AI
45. Section Preview
46. Access Control Principles for AI
47. AI Access Control Models
48. Threat Landscape of AI Systems
49. Model Access
50. Data and Agent Access
51. Network and API Access
Chapter 8: Applying Data Security Controls and Perform
Monitoring & Auditing for AI Systems
52. Section Preview
53. Overview of AI Data Security Controls
54. Encryption of AI Data
55. Data Safety Measures
56. Prompt & Log Monitoring
57. Performance & Cost Monitoring
58. AI Cost Monitoring
59. Quality & Compliance Auditing
Chapter 9: MODULE 4 - Distinguishing AI-Related Threats &
Compensating Controls
60. Section Preview
61. Data Security Considerations
62. AI Life Cycle Security Considerations
63. The Human Role in AI Security
64. Ethical Considerations in AI Design
Chapter 10: Analyzing AI System Attacks & Utilize Compensating
Controls
65. Section Preview
66. Analyzing AI Attacks
67. Backdoor & Trojan Attacks
68. Model & Data Poisoning
69. Model Inversion & Model Theft
70. AI Attacks Analysis & Controls
71. Applying Compensating Controls
Chapter 11: MODULE 5 - Leveraging AI in Security &
Understanding its Misuse
72. Section Preview
73. AI Tools in Security Operations
74. AI Use Cases: Detection & Analysis
75. AI Security Use Cases
76. AI Use Cases: Testing & Management
77. AI and Incident Management
78. AI for Deception and Social Engineering
79. AI for Reconnaissance & Data Correlation
80. AI for Automated Attacks
Chapter 12: Use of AI to Automate Security Tasks
81. Section Preview
82. AI for Security Scripting and Content Summarization
83. AI in Security Workflows
84. Automate Security Tasks
85. AI in DevSecOps
Chapter 13: MODULE 6.0 - Understanding AI Governance, Risk &
Compliance
86. Section Preview
87. Establish AI Governance
88. Important Roles in AI
89. AI Governance
90. Principles of Responsible AI
91. Identifying Risks Unique to AI
92. Putting Principles into Practice
93. Common AI Risks
Chapter 14: The Impact of Compliance on Business Use and
Development of AI
94. Section Preview
95. Common Themes in AI Regulation
96. Important AI Compliance Frameworks
97. Organizational AI Policies
98. External Compliance Impacts
Chapter 15: FINAL EXAM
99. Conclusion
DATES
Published : 2026-03-30
Last Updated : 2026-03-30
If you fear the truth, dont come to my well.
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