type: BadgeClass
id: https://api.badgr.io/public/badges/pQ30YIeeTGO1l_Yhp-4dJA
name: Artificial Intelligence & Cybersecurity
image:
  id: https://badges.parchment.com/public/badges/pQ30YIeeTGO1l_Yhp-4dJA/image
image alt text: Artificial Intelligence & Cybersecurity badge image
achievement type: Badge
description: Through a partnership with the Dendritic: A Human-Centered AI and Data Science Institute, Florida Gulf Coast University offers the Artificial Intelligence & Cybersecurity micro-credential to individuals who participated in the academy program, completing the 8-10 hour training and displaying proficient skills in applying AI-driven techniques to cybersecurity challenges, including threat detection, incident response, adversarial AI, and ethical considerations in security applications.
issuer: https://api.badgr.io/public/issuers/yOtRE461QKC-ZV7tv9Cy9w
alignment:
  target name: Anomaly detection
  target url: https://talentneuron.com/
  target description: Anomaly detection is the ability to recognize and flag unusual data patterns or behavior that deviate from expected norms, often using statistical or machine learning methods.
  target framework: TALENT_NEURON
  target code: TN-35942
alignment:
  target name: AI Risk Management
  target url: https://talentneuron.com/
  target description: AI Risk Management is the process of recognizing and addressing potential risks and ethical concerns related to artificial intelligence systems.
  target framework: TALENT_NEURON
  target code: TN-67219
alignment:
  target name: Threat intelligence
  target url: https://talentneuron.com/
  target description: Threat intelligence is the process of gathering and analyzing information to anticipate and counter potential security threats in various contexts.
  target framework: TALENT_NEURON
  target code: TN-42461
criteria:
  narrative: **Learning Objectives:** • Understand the fundamentals of AI in cybersecurity: opportunities, limitations, and threat models • Apply machine learning and deep learning for intrusion detection and anomaly detection • Use AI-enabled threat intelligence, malware analysis, and automated incident response strategies • Recognize and address adversarial AI: evasion, poisoning attacks, and robustness of security models • Apply AI-driven monitoring to Edge/IoT and smart system security • Integrate human-centered AI principles and ethical considerations in cybersecurity applications **Earning Requirements** Participants will master these skills by the successful completion enrolled in the fully online course, including the review of all module learning materials and completing the final capstone project. The capstone project requires participants to design an AI-driven cybersecurity solution or threat analysis framework, with a written report addressing ethical considerations.