Aerospace engineering is a complex field involving many disciplines, such as aerodynamics, structures, propulsion, avionics, flight dynamics. etc., which are taught as separate courses. The current paradigm for teaching aerospace engineering is to cluster the different disciplines and focus on them in separate courses, which leads to fragmentation and a loss of context of an overall design problem of a transport vehicle. The primary objective of this project is to integrate the different disciplines taught in aerospace engineering courses into one computational platform that can be used by instructors and students for the purposes of collaborative teaching and projects. The platform is designed with ease of use and clarity to help students become familiar and comfortable with basic programming, and yet transparent enough for them to understand the rationales and computational details behind the algorithms. This is in contrast with some commercial software where students can provide inputs and run the analyses without necessarily understanding the concept behind it. Furthermore, we can also use this platform to introduce computational paradigms that are necessary in any engineering industry today (e.g., optimization, sensitivity analysis, machine learning and artificial intelligence) by demonstrating their usages in the context of aerospace engineering applications. A secondary objective of this project is to develop a large-scale aircraft design optimization problem that will be an effective example for all courses to use. This platform will allow different courses to focus on their disciplines in a holistic approach by using the design optimization problem, in which the effects on other disciplines are observed by changes in the variables of the discipline in focus.