Masters of Science in Applied Data Science for Business (MS ADSB)

Masters of Science in Applied Data Science for Business (MS ADSB)

Learning Goals & Objectives

LG1: Technology Knowledge 

MSADSB graduates will demonstrate an understanding of technologies and how they influence business practice such as a basic understanding of blockchain technology, analytics, or Machine Learning.

Learning Objectives:

1. Familiarity with transformative technology: Students will exhibit a general understanding of how a technology that can cause digital transformation functions.
2. Application of transformative technology to business practice: Students will be able to understand the interaction between a transformative technology and a business practice. 
3. Interpretation of the managerial significance of successful implementation of a transformative technology: Students will be able to extend their understanding of implications of technology adoption to analyze the strategic importance of transformative technologies.

LG2: Knowledge about Ethics, Privacy, and Security issues pertaining to data 

MSADSB graduates will understand how to ethically manage data consistent with laws and privacy standards.

Learning Objectives:

1. Conversant in regulation-, security-, and privacy-related provisions of data management:  Students will learn the major US and global rules and norms governing data management and their implications.
2. Able to employ ethical frameworks:  Students will develop an understanding of how ethical decision-making can influence data usage and storage. 
3. Formulation of a managerial response to a violation:  Students will be able to craft a response to a scenario involving a privacy, security, or ethical breach related to data management (including communications to stakeholders, remedies, and future breach avoidance). 

LG3: Critical Thinking 

MSADSB graduates will demonstrate strong critical thinking skills required to navigate changing business practices in the face of digital transformation including AI, IoT, big data, cloud services, etc.  They will understand how business models may change due to digital transformation.

Learning Objectives:

1. Description or clarification of the problem:  Students will be able to describe and clarify the problems to be analyzed.
2. Interpretation and evaluation of information:  Students will interpret and evaluate information to develop a coherent analysis or synthesis.
3. Organization of evidence:  Students will organize evidence to reveal important patterns, differences, or similarities.
4. Conclusions and recommendations:  Students will logically tie conclusions/recommendations to the analysis.