The overarching objective of this course is to teach students the art and science of planning, developing, and deploying object-oriented Python programs for business applications.

Myriad multinational technology, social-media, and finance corporations have adopted Python programming for its simplicity, expressiveness, and rapidity with which application programs may be developed, particularly through object- oriented programming. This programming style generates robust software by combining self-contained and independently developed and validated mini programs called objects, which are intended to represent real- world items that interact with one another within a comprehensive program.

Hence, an object-oriented program is analogous to a company that fulfills its mission through the interaction of its clearly delineated corporate departments, like finance, marketing, and operations management. In this analogy, the corporate departments represent the software objects, each of which possesses its own data and functions.

This course will cover the application of object-oriented Python programming to solve linear and non-linear business and quantitative-economics problems from a variety of fields, including, but not limited to, Econometrics, Finance, Macroeconomics, and Microeconomics. Also presented will be an introduction to the application of Python to solve problems in dynamic economics and financial engineering. In the course, students will deepen their Python programming expertise through daily hands-on coding activities using the free comprehensive Spyder Integrated Development Environment (IDE), for Windows and Mac, and a set of Python program templates provided by the lecturer.