IntroAI:DesignPrinciplesAppl

3 Credits · Level: Graduate

This course introduces Machine Learning (ML) and Artificial Intelligence (AI) by opening up the design principles and key concepts that make the technologies possible and enable all the applications we use. This course is especially designed for students from non-technical backgrounds. Students will learn methods for “deblackboxing” the complexity of ML/AI systems by breaking down the larger systems of computing and data into the subsystems that are combined to create the processes that happen “blackboxed” between our inputs and outputs. Students will learn the main building blocks of all contemporary ML/AI systems: data encoding (how text and images become computable data), pattern recognition, and the computational methods (based on statistics and probabilities) for analyzing large data sets and generating responses as outputs from our prompt inputs. Students will learn the “why” and “how” in the designs for “generative AI” (Gen AI) systems (like ChatGPT, DALL-E, Claude, and Stability), and how we can use these applications for research and creativity. We will do many “hands on” experiments with the AI/ML systems, and students will develop their own research projects for understanding and applying the systems. We will also study the important ethical issues for ML/AI, beginning from an important foundation: ethics must always start with the truth about the technologies themselves. Outcomes: By the end of the course, students will have gained the core knowledge of the design principles of AI/ML systems, and will be prepared to use the applications in their own fields and careers in informed and critically aware ways. Students will also be prepared to participate in developing new applications in AI/ML, and be able to critique applications for their ethical and political consequences. In addition to attaining conceptual and applied knowledge for AI/ML systems, students will also achieve the competency for being explainers and communicators of truthful explanations of ML/AI technologies, a competency now greatly needed in every field and profession.