Advanced mathematical concepts essential for understanding and applying techniques in machine learning using Python programming language. Focus on vector-based calculus, probability distributions, continuous optimization, and information theory. Prerequisites: A grade of C or better in (AIM250 and MAT227) or permission of Program Director.

Examination of deep learning algorithms and Python applications. Emphasis on data input, algorithm selection, hyperparameter tuning, and deep learning model evaluation and selection. Prerequisites: A grade of C or better in AIM250 or permission of Program Director.

Examination of vision with computers utilizing Python tools and libraries. Emphasis on image processing and feature detection as it applies to various computer vision tasks, utilizing visualizations for transparency. Includes statistical and deep computer vision techniques. Prerequisites: A grade of C or better in (BAM310 and BAM/MAT305) or permission of Program Director.

Examination of natural language processing utilizing Python tools and libraries. Emphasis on computer linguistic understanding as it applies to various natural language tasks. Statistical and deep natural language techniques will be covered including large language models. Prerequisites: A grade of C or better in (BAM310 and BAM/MAT305) or permission of Program Director.

Explores advanced techniques in parallel computing for optimizing performance in machine learning applications. Focus on design, implementation, and evaluation of parallel algorithms across various hardware architectures, including CPUs, GPUs, and custom artificial intelligence accelerators. Includes hands-on projects and real-world case studies to develop the skills necessary to leverage parallel computing effectively to accelerate machine learning tasks. Prerequisites: A grade of C or better in CSC/EEE230, CSC240++, BAM/MAT305, and BAM310.

Explores optimization path for automation. Covers a diverse array of techniques including evolutionary algorithms, reinforcement learning, and swarm intelligence to navigate complex environments. Emphasis on hands-on projects and theoretical exploration, including design and implementation of optimized paths. Prerequisites: A grade of C or better in CSC310, BAM/MAT305, and BAM310.

Capstone project with opportunities for research and application of artificial intelligence and machine learning knowledge and skills obtained throughout the student's program of study. Focus on project research, selection, design, and implementation with emphasis on communication, critical thinking, and technical skills. Prerequisites: A grade of C or better in BAM320, BAM330, and CSC310.

Completion of capstone project using research and application of artificial intelligence and machine learning knowledge and skills obtained throughout the student's program of study. Focus on project testing, enhancement, and evaluation. Emphasis on self-assessment, development of a written report, project defense, and career development. Prerequisites: A grade of C or better in BAM490.