Teaching

Course Descriptions

24-787: Artificial Intelligence and Machine Learning for Engineering Design

12 Units

This course will cover fundamental artificial intelligence and machine learning techniques useful for developing intelligent software tools to support engineering design and other engineering activities. The computational techniques covered include: search, constraint satisfaction, probability, data mining, pattern recognition, neural networks, optimization, and evolutionary computation. The course will examine both the theory behind these techniques and the issues related to their efficient implementation. The application of the techniques to engineering tasks, such as design representation and automation will be explored. In addition to regular homework sets, the course includes individual paper presentations and a substantial term project in which the student will develop an intelligent software tool to support an engineering task. A basic working knowledge of a scientific programming language (C/C++, Java, Matlab) is highly recommended.

24-441: Engineering Design II: Conceptualization and Realization

12 Units

This course guides students through the design process in the applied design of a practical mechanical system. Lectures describe the typical design process and its associated activities, emphasizing methods for innovation and tools for design analysis. Professional and ethical responsibilities of designers, interactions with clients and other professionals, regulatory aspects, and public responsibility are discussed. The design project is typically completed in teams and is based on a level of engineering knowledge expected of seniors. Proof of practicality is required in the form of descriptive documentation. Frequently, a working model will also be required. Oral progress reports and a final written and oral report are required.