AIT : Artificial intelligence Track
Program Overview
Cyber threats are evolving rapidly, and organizations need skilled professionals who can protect systems, data, and users.
Our cybersecurity curriculum emphasizes:
Core IT, networking, and operating system fundamentals
Defensive security concepts and threat awareness
Security operations, monitoring, and incident response
Cloud and hybrid security principles
Governance, risk, and compliance (GRC)
Students gain hands-on experience through labs, simulations, and scenario-based exercises that mirror real-world security environments.
AIT : Artificial intelligence Track
Objective
The AIT program introduces students to foundational and applied concepts in artificial intelligence, with a focus on practical skills relevant to security and enterprise applications. Graduates will understand AI architectures, neural networks, natural language processing, large language models, and AI-driven security workflows. They will be prepared to leverage AI safely and effectively in real-world environments, bridging technical knowledge with organizational needs.
AIT 100 : AI Foundations
Prerequisites: CYB 100 (Cybersecurity Foundations)
This course introduces students to neural networks, natural language processing (NLP), large language models (LLMs), and self-hosting LLMs. Students learn core AI concepts and architectures, practice neural network training, and explore word embeddings, recurrent neural networks, and transformer models. Labs include hands-on exercises with AI model training, attention mechanisms, and system prompts, giving students practical experience in AI development and deployment.
AIT 105 : AI Hands-on for Security
Prerequisites: AIT 100 (AI Foundations)
AIT 105 focuses on applying AI safely and effectively in cybersecurity contexts. Students explore AI vulnerabilities such as prompt injection, token theft, and excessive permissions, and gain hands-on experience with NLP-based triage and AI-augmented incident response. The course covers AI architecture, RAG, agentic systems, prompt engineering, and practical security assessments. By the end, learners can evaluate AI solutions intelligently, implement AI systems safely, and act as informed advisors on AI security decisions.