(PhD) Computing For Business Research

This course is designed to teach students essential concepts of computer programming and computational analytics that will be useful in carrying out research and other work. This work often involves: • Gathering, organizing, and analyzing data • Using numerical algorithms for analysis (e.g., regression, simulation, optimization, etc.) • Generating and presenting results using tables, graphs and reports This course will prepare students to correctly and efficiently carry out these tasks. The course includes the following topics: • Students will learn programming concepts for research and other work. • We will give an overview and comparison of languages, tools and libraries such as Python, Bash, C, C++, Matlab, SQL, TensorFlow, etc. • We will cover principles of software design, such as testing and debugging. • You will also learn how to choose between and use available tools/platforms and analytic methods to complete computing tasks efficiently. • We will also cover a breadth of computational techniques such as k-nearest neighbors (k-NN), logistic regression, basic optimization and simulation, k-means clustering and neural networks. The work for the course includes weekly individual assignments. The prerequisites are prior programming experience. We will also assume that students have prior knowledge of basic linear algebra and statistics. We welcome students from all divisions and departments. Business school students will have priority when registering.