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This hands-on course examines the technologies and infrastructure required to support digital innovation.  The course examines the major components of the information technology infrastructure, such as networks, databases and data warehouses, electronic payment, security, and human-computer interfaces.  The course covers key web concepts and skills for designing, creating and maintaining websites, such as Grid Theory, HTML5, CSS, JavaScript, AJAX theory, PHP, SQL and NoSQL databases.  Other principles such as Web Accessibility, Usability and User eXperience, as well as best security practices, are explored in detail through a combination of lectures, in-class examples, individual lab work and assignments, and a final group project.

The overall aim of this course is to develop a high-level understanding of the dynamics of innovation, the distribution and outcomes of the strategic management of innovation and the relationships that are important in developing high-impact organizations. 

Emerging technologies鈥攕uch as digital media, the 鈥渋nternet of things鈥�, artificial intelligence (AI), and financial tech鈥攁re playing an increasingly central role in how individuals live and interact with each other; how businesses innovate and create new opportunities; and how governments function and serve their populations. But the unrestrained development and use of these technologies can raise complex legal, policy, and ethical challenges. This course offers students an introduction to foundational legal, policy, and ethical issues raised by emerging technologies in a variety of contexts, with special consideration for digital innovation and commerce. On completion, students will be able to better identify, understand, and critically assess these issues and also more effectively manage and resolve them in the course of the professional pursuits.

This course covers essential statistical methods for medical research. Topics include descriptive analysis techniques and basic principles of statistical inference for comparison of means, proportions and investigation of relationships between variables using regression mod-eling techniques. Students will also become familiar with nonparametric tests and power and sample size calculations.

This core digital innovation course focuses on the design and management of digital innovation projects for both public sector and private sector organizations. Specifically, this course provides students with knowledge and skills to initiate and execute digital innovation and transformation projects in existing organizations or new start-ups.

This course is designed to bring students interested in a diversity of DIgital Innovation (DI) application areas to collaborate in a digital innovation process. The main objective is to synthesize knowledge in DI, apply to an area that may be different than the team members鈥� expertise, and expand student鈥檚 skill set and attitudes through cross-pollination.

This course is based on the design of the 鈥淢anagement Without Borders鈥� course, with credit to its material.

This class will provide Master of Digital Innovation thesis students with an understanding of the principles of empirical science as they relate to computer science related research. The goal is for the student to determine the research methods most appropriate for their research area and to be able to design simple to moderately complicated research studies. The course covers both quantitative and qualitative research issues and will provide a practical introduction to the statistics through hand-on tutorials. In addition, this course will provide the basis for critical reading of research findings in the literature and students will gain experience with scientific writing.