My E-Portfolio based on work carried out on my Msc Program on Artificial Intelligence and Machine Learning at the University of Essex.
My E-Portfolio based on work carried out on my Msc Program on Artificial Intelligence and Machine Learning at the University of Essex.
Foundational computing concepts and programming fundamentals essential for artificial intelligence studies, including data structures, algorithms, and computational thinking principles that underpin advanced AI methodologies.
Comprehensive exploration of artificial intelligence fundamentals, covering key concepts, methodologies, and theoretical frameworks that define modern AI systems and their applications across various domains.
Advanced mathematical techniques and numerical methods essential for AI implementation, including linear algebra, calculus, optimization algorithms, and statistical methods used in machine learning and data analysis.
Comprehensive study of machine learning algorithms, techniques, and practical applications, covering supervised and unsupervised learning, neural networks, and real-world implementation projects with hands-on experience.
Design, development, and application of intelligent agent systems, including agent models, AI foundations, real-world deployment, and current research in agent-based computing.
Advanced study of knowledge representation methods, logic programming, ontology development, and reasoning techniques with practical applications in artificial intelligence systems and semantic web technologies.
Comprehensive study of research methodologies, statistical analysis, professional ethics, and practical skills for conducting rigorous research in computing and related fields, including literature reviews, survey design, and data visualization.
Final dissertation artefacts for an encoder-based policy guardrail for autonomous web agents, including the dissertation, defense deck, benchmark-grounded PCM pipeline, trained model, and focused SuiteCRM pilot.