Artificial Intelligence, Advanced

Artificial Intelligence, Advanced is a continuation of Artificial Intelligence Fundamentals and is designed for students ready to deepen their understanding of how intelligent systems are built, trained, and evaluated. This course explores the evolution of artificial intelligence (AI) from early expert systems to modern machine learning and deep learning models that power today’s technologies. Students will investigate core concepts including data collection and preparation, supervised and unsupervised machine learning, neural networks, deep learning architectures, and natural language processing (NLP). Additionally, students will critically examine the ethical implications of AI, including its potential for bias, lack of transparency, privacy concerns, and other societal effects. Through hands-on activities, real-world case studies, and collaborative problem-solving, students will gain practical experience in designing and analyzing AI solutions. A capstone project challenges students to identify a real-world problem and design, develop, and present an AI-based solution. Contextual instruction and student participation in co-curricular career and technical student organization (CTSO) activities will develop leadership, interpersonal, and career skills. High-quality work-based learning (HQWBL) will provide experiential learning opportunities related to students' career goals and/or interests, integrated with instruction, and performed in partnership with local businesses and organizations.