Students are to learn the fundamentals of drone-based computer languages, such as the C languages, Ruby on Rails, and Python through applied application. Students will explore within the organizational framework, the most effective languages for integrating and communicating drone-based processes, and efficiency in terms of scalability for technology commercialization.

Students will work within organization to introduce artificial intelligence and write reports on the feasibility of integrating AI for new and existing use cases for drone-based products and/or services to enhance productivity and efficiency. Students may write original algorithms and conduct machine learning utilizing visual and pattern recognition technology for the purpose of commercial applications.

Students will work with the creation of artificial neural networks and deep learning applications in the field. Students will conduct assessments and reports regarding the potential for cognitive applications to be used within organizational work environments, as well as utilizing robots for depth perception and solutions for logistics and supply chain management. Students will also explore the feasibility of integrating IBM’s Watson supercomputer into commercial drone applications, which is capable of speech to text, visual recognition, emotional intelligence, and other varied services.

Students will work to solve real-world workplace problems, and providing industry solutions through the applied development of IoT applications, prototype development and Lean business model development, for the conceptual design and potential implementation of IoT technology into the organizational structure and business vision.

Students will become exposed to various types of propulsion systems for aquatic, amphibious, land, air, low-orbit, and space-based autonomous systems. Specifically, students will focus on a common thread in each module, concerning an emphasis on sensory localization in dynamic environments.

Students will learn about emerging technologies within the commercial drone sector, and how to adapt organizational behavior, strategy, or resource allocation in order to maximize future opportunities and product value. Students will work with emerging technologies such as edge computing, swarm technology, quantum computing, blockchain technology, cyber security for embedded systems, virtual reality, and augmented reality to name a few.

Students will work on original, proprietary, or open-source research topics, and/or the development of commercial drone prototypes utilizing any of the development languages, engineering techniques, artificial intelligence and machine learning models for the furthering of the student learning experience, benefit of potential or current employers, and overall advancement of the overall STEM eco-system and Commercial Drone industry in America.