AI-Augmented Cybersecurity Professional
Use AI to work faster, detect more, and respond better. Eight modules covering prompt engineering, AI threat detection, defensive AI, red teaming, and AI-driven incident response. For working security professionals ready to add AI to their toolkit.
30-day refund if you complete Module 1 and it is not right for you. No questions asked.
What you will build
Each module produces practical assets you can deploy immediately: prompt libraries, detection templates, playbooks, and governance frameworks built for real security work.
Salary ranges are illustrative estimates based on industry job posting data and BLS Occupational Employment and Wage Statistics, 2024. AI security roles are emerging and compensation varies significantly by employer, location, and experience. For educational purposes only. See full salary data
All 8 modules
Click any module to see what you learn and the deliverables you walk away with. Each module ends with a quiz and produces at least two keeper artifacts.
1. AI for Security Professionals: The Field
Map the AI tools security teams use today, distinguish between hype and production-ready capabilities, and build your personal AI stack audit.
- AI in Security: State of the Field
- LLMs vs. ML vs. Rules-Based Systems
- Evaluating AI Tools for Security Use
- Your Personal AI Tool Stack
- AI Risk and Governance Primer
2. Prompt Engineering for SecOps
Write prompts that get reliable, security-relevant outputs from AI systems. Build a reusable SecOps prompt library for your team.
- Why Prompting Matters in Security Workflows
- Prompt Structure for Technical Analysis
- Context, Constraints, and Output Formats
- Chain-of-Thought for Incident Analysis
- Building Your SecOps Prompt Library
3. AI-Powered Threat Detection
Use AI to write detection rules, analyze logs faster, and surface anomalies that signature-based tools miss. Build detection templates you can deploy.
- AI vs. Signature Detection: What Each Does Best
- Using LLMs to Write SIEM Rules
- Log Analysis at Scale with AI Assistance
- Anomaly Detection: Models and Thresholds
- Detection Templates for Common Attack Patterns
4. Defensive AI Security
Understand how attackers target AI systems, how to assess AI model risk, and how to build controls into AI-enabled environments.
- Attack Surface of AI Systems
- Prompt Injection and Jailbreak Techniques
- Model Poisoning and Data Integrity
- Assessing AI Risk in Enterprise Environments
- Controls Framework for AI Deployments
5. AI Red Teaming and Offensive Techniques
Apply AI tools to reconnaissance, payload generation, and vulnerability analysis in authorized engagements. Build an adversarial testing framework.
- AI-Assisted Reconnaissance
- Using AI for Payload Variation
- Automated Vulnerability Analysis
- AI in Social Engineering Scenarios
- Building Your Adversarial Testing Framework
6. AI-Augmented Incident Response
Speed up IR with AI-assisted triage, timeline reconstruction, and report generation. Build a playbook that integrates AI into each phase of response.
- AI Triage: Prioritization and False Positive Reduction
- Timeline Reconstruction with AI Assistance
- Evidence Summarization for Non-Technical Stakeholders
- AI-Assisted Threat Actor Attribution
- Building Your AI-Integrated IR Playbook
7. Building AI Security Programs
Design governance frameworks, evaluation criteria, and team training plans for organizations deploying AI in security operations.
- AI Security Program Structure
- Vendor Evaluation for AI Security Tools
- Team Skill Gap Analysis for AI Adoption
- Governance, Policy, and Acceptable Use
- Change Management for AI Integration
8. AI Security Career Strategy
Position yourself for roles at the intersection of AI and security. Build your portfolio and identify the fastest career paths in AI security.
- Emerging Roles: AI Security Engineer, Red Team AI Specialist
- Skills That Command Premium Compensation
- Building an AI Security Portfolio
- AI Security Certifications: What Exists and What Matters
- Your 18-Month AI Security Career Plan
What makes this different
Most AI content for security teams is either too abstract or too focused on building models. This course teaches you to use AI as a working security professional.
Every module produces something you can use Monday morning: prompts, templates, playbooks, and frameworks built for real security work.
You do not need a machine learning background. The course is written for security practitioners who want to use AI tools, not build AI models.
You learn both how to use AI to defend and how attackers are using AI to attack. The red teaming module covers authorized engagements only.
Module 8 maps the fastest-growing AI security roles, what they pay, and what skills move you from security professional to AI security specialist.
Prompt libraries, playbooks, risk frameworks, and governance templates you can deploy immediately or adapt for your organization.
This course is for you if...
- ✓You work in cybersecurity (SOC analyst, IR, pen tester, security engineer) and want to use AI tools daily
- ✓You are a security manager who needs to evaluate AI tools for your team
- ✓You want to specialize in AI security roles before they become mainstream
- ✓You are running penetration tests and want to understand where AI fits in authorized engagements
- ✓You need to build AI governance and acceptable use policies for your organization
- ✓You want to position for senior roles that increasingly require AI literacy
This course is NOT for you if...
- ✕You have no cybersecurity background. Start with Break In first.
- ✕You want to build AI or machine learning models from scratch
- ✕You want a vendor certification like CompTIA AI+ or similar
- ✕You are looking for in-depth ML theory or statistical modeling
- ✕You expect guaranteed employment outcomes (no course can promise that)
About the instructor
Julian Calvo holds an Ed.D. in Applied Learning Sciences from the University of Miami, with research focused on psychometric assessment design and adult learning frameworks. The AI-Augmented course draws on his work building AI-integrated systems into the DecipherU platform and his study of how security teams are adopting AI tools across detection, response, and red team operations.
Complete Module 1 and if the course is not what you expected, email us within 30 days of purchase. Full refund, no questions asked.
Module 1 gives you a real sample of the course depth and methodology. If the approach does not fit your situation, the rest will not be different.
Frequently asked questions
No. The course is written for security practitioners, not AI researchers. You need a basic understanding of cybersecurity concepts. The course teaches you to use AI tools as a working security professional, not to build AI systems from scratch.
The course assumes you understand core security concepts: what a SOC does, what incident response involves, what a penetration test is. If you are brand new to cybersecurity, start with the Break In course first, then return to this one.
Module 5 covers AI-assisted red teaming for authorized engagements only. All offensive techniques are framed in the context of legitimate penetration testing and authorized security assessments. Nothing in the course is designed for or intended to support unauthorized access.
Most students complete it in 3-6 weeks working a few hours per week. There is no deadline. Lifetime access means you can return to any module when you need it.
No. No course can guarantee employment or promotion outcomes. Career results vary by individual effort, employer, local market, and factors outside any course. This course is for educational purposes only.
Ready to add AI to your security work?
Start with the free career assessment to confirm this is the right next step.
Career transition timelines and outcomes vary by individual. This guide is for educational purposes and does not guarantee employment outcomes.