M.S. in International Business & Entrepreneurship and M.S. in Information Systems Dual Degree Master's Program

This course will focus on Data Mining & Knowledge Discovery Algorithms and their applications in solving real world business and operation problems. We concentrate on demonstrating how discovering the hidden knowledge in corporate databases will help managers to make near-real time intelligent business and operation decisions. The course will begin with an introduction to Data Mining and Knowledge Discovery in Databases. Methodological and practical aspects of knowledge discovery algorithms including: Data Preprocessing, k-Nearest Neighborhood algorithm, Machine Learning and Decision Trees, Artificial Neural Networks, Clustering, and Algorithm Evaluation Techniques will be covered. Practical examples and case studies will be present throughout the course.

This 2-credit course focuses on data and database management, with an emphasis on modeling and design, and their application to business decision making. The course provides a conceptual understanding of both organizational and technical issues associated with data. The central theme concerns data modeling and databases. We examine organizational approaches to managing and integrating data. Among the topics included are normalization, entity-relationship modeling, relational database design, SQL, and data definition language (DDL). Discussed are specific applications such as strategic data management, master data management, and physical database design. The course concludes with a brief overview of Decision Support Systems, data warehousing and business intelligence, NoSQL databases (e.g., MongoDB) and cloud computing. The course includes a number of cases studies and modeling and design projects. Students in MIS 631 must also enroll in the associated 1-credit lab course MIS 632 Managing Data Lab.

This 1-credit lab course provides an experiential learning component for MIS 631 Data Management for which it is a co-requisite. MIS 632 provides hands-on experience in designing, implementing, and querying data bases. The relevant software is introduced using demonstrations, in-class exercises and homework exercises that are closely tied to and executed in synch with the conceptual and theoretical material covered in MIS 631. Specifically, students will gain hands-on experience in: (i) ERWIN - a widely used commercial tool for representing conceptual (e.g., E-R diagrams) and logical data models (e.g., relational DBMS), (ii) PostgreSQL (relational database software), (iii) SQL Structured Query Language) and (iv) MongoDB a NoSQL document data store. Students in MIS 632 must also be enrolled in the associated 2-credit lecture course MIS 631 Managing Data course.

This course focuses on the issues surrounding the design of an overall information technology architecture. The traditional approach in organizations is to segment the problem into four areas - network, hardware, data and applications. This course will focus on the interdependencies among these architectures. In addition, this course will utilize management research on organizational integration and coordination science. The student will learn how to design in the large, make appropriate choices about architecture in relationship to overall organization goals, understand the different mechanisms available for coordination and create a process for establishing and maintaining an enterprise architecture.

Corporate financial management requires the ability to understand the past performance of the firm in accounting terms; while also being able to project the future economic consequences of the firm in financial terms. This course provides the requisite survey of accounting and finance methods and principles to allow technical executives to make effective decisions that maximize shareholder value.

510205 - Transformative Innovation (9 ECTS)

510206 - Innovation & Technology Law (6 ECTS)

Analysis of most pressing contemporary issues that the law faces when regulating global, technology enabled markets, the digital economy and knowledge industries. By the end you will have acquired a sophisticated awareness of the problems that arise in the field of law and technology and the differing approaches to their solution.

507903 - Firm Valuation And Capital Market Instruments (9 ECTS)

The course has two main objectives. On one side to illustrate the topic of firm valuation. On the other to give an idea of financial instruments negotiated in financial markets, grouped in asset classes. At the end of the course, students will be able to operate the valuation of a firm using the DCF and market multiples. At the same time, students should be able, at the end of the course, to understand the main features of the most important asset classes.

507909 - Big Data Analysis (9 ECTS)

Knowledge of the most relevant statistical methods for large data set analysis. The student will learn how to run a complete work flow of analysis by employing R software. From the collection and management of large data set, through the choice of the most appropriate models to the final interpretation and contextualization of the results.

500253 - Economics Of Emerging Economies (9 ECTS)

To understand the complexity of economic development and the deep factors behind the failure or success of nations. Furthermore, the class aims to apply the acquired knowledge in the assessment of various cases of development considering, in particular, the need for an interdisciplinary methodology and the lack of any single approach to the solution of the problems of development.

508750 - Information Systems For Managers (9 ECTS)

This course aims to start you on your way to becoming a competent and IS-savvy manager who is well versed in the analysis of the potential and risks of constantly evolving Information Technologies. The class foundation is in Information System discipline, upon which you can build further through formal or independent studies.

510196 - Applied Project Management And Agile Methods (6 ECTS)

510207 - Coding And Database Management (6 ECTS)

The course is designed to be practically theoretical. We will cover enough theory to develop a frame of reference on which to build practical skills. In parallel, through exercises and projects, we will internalize theoretical concepts and reinforce our theoretical understanding.

Can be transferred from Stevens MIS631 and MIS632

508650 - Corporate Finance (6 ECTS)

Can be transferred from Stevens FIN515

504835 - Economics Of Innovation And Industrial Dynamics (6 ECTS)

Can be transferred from Stevens Economics Elective Course

509363 - Business Analytics With Excel (3 ECTS)

Can be transferred from Stevens MIS637

510208 - Digital Marketing And Crypto Strategies (6 ECTS)

Can be transferred from Stevens Elective Course

Elective Courses (12 ECTS)

Can be transferred from Stevens Elective Courses

500000 - Master Thesis (24 ECTS)