MKT3574 Customer Acquisition and Persuasion
(Formerly Managing the Sales Process)
4 Advanced Management CreditsCustomer acquisition and retention is the driver of revenue and hence the lifeblood of every company. Therefore, organizations continuously seek people with strong persuasion skills. College graduates often become sales professionals, business development executives, customer relationship managers, or end up in positions that complement these roles. In addition, many entrepreneurs realize, often too late, the critical role of professional selling for the growth and survival of their nascent ventures. This course will equip students with the knowledge and skills to excel in professional selling, business development, and entrepreneurship.
Prerequisites: MKT 2000
- Program: Undergraduate
- Division: Marketing
- Level: Advanced Elective (UGrad),Advanced Management (UGrad)
- Course Number: MKT3574
- Number of Credits: 4
MBA9502 Customer Acquisition and Persuasion
(Formerly Selling Ideas, Products and Services to Executives)
1.5 CreditsThe growth of business revenue depends directly on a firm's ability to create additional value for
current and potential customers. This course will focus on the professional selling process, to include identifying opportunities, gaining access to and engaging decision makers, asking high gain questions, building long term relationships with decision makers and influencers, presenting winning proposals, handling resistance and objections, completing the sale or obtaining commitments and following up. The course will use the value creation methodology to identify solution options aimed at creating value and enhancing the other party's (e.g., customers) competitiveness. The course will use a number of inputs to share current academic thinking and best practice. Course participants will also be challenged to apply the learning to potential opportunities. The art and science of ethically and effectively convincing another party about self, ideas, solutions, products, services, etc., is an imperative for everyone, whether in family or social settings, profit or not-for-profit ventures. It's a life skill. This course is therefore for everyone.
Prerequisites: None
- Program: Graduate
- Division: Other
- Course Number: MBA9502
- Number of Credits: 1.5
OIM3620 Cybersecurity
4 Advanced Liberal Arts Credits
Teaches students the relevance of purpose to and means behind establishing higher security levels for computers and associated networks. The nature of various security breaches including hacker attacks, email worms and computer viruses are explored. Management's responses including policy and procedure creation, risk management assessment and personnel training program design among others are examined. The tools of both security violators and protectors are explored. This course probes deeply into technical aspects of the hardware and software required to support computer networks. The course uses a combination of readings, case studies, class discussion and guest speakers for learning.
Prerequisites: (SME2012 or OIM2000) and (QTM1000 or AQM1000)
- Program: Undergraduate
- Division: Operations and Information Management
- Level: Advanced Elective (UGrad),Advanced Liberal Arts (UGrad)
- Course Number: OIM3620
- Number of Credits: 4
OIM7556 Cybersecurity
1.5 Elective Credits
The course is designed for the next generation managers who need to appreciate both the technical aspects and business impacts of cybersecurity in the enterprise. Different types of security break from a manager's perspective are explored. Students will also learn to design or support cybersecurity initiatives such as a risk management, policy creation, incident response and continuous improvement. The course uses a combination of readings and current events, class discussion and quest speakers for learning.
Prerequisites: None
- Program: Graduate
- Division: Operations and Information Management
- Level: MSBA Elective (Grad),Graduate Elective (Grad)
- Course Number: OIM7556
- Number of Credits: 1.5
QTM6110 Data Exploration (Quantitative Methods)
MSEL Course
1.5 CreditsData is valuable when it is used to make good decisions and avoid bad ones. We consider the value of data as a resource by studying how the variety of information available can be displayed, interpreted and communicated. Students will see the different approaches suggested by both traditional statistical methods and the recent advances in big data analytics. The course will emphasize the ways in which managers and entrepreneurs are both producers and consumers of data.
- Program: Graduate
- Division: Mathematics Analytics Science and Technology
- Course Number: QTM6110
- Number of Credits: 1.5
QTM 3600: Data Science Field Project
4 Advanced Liberal arts credits
The course will provide students with the opportunity to reinforce their skills in data science, including but not limited to data acquisition, data preparation/wrangling, exploratory data analysis/visualization, model building, testing, presentation, and deployment by coaching them through a real-world, data-intensive project. The course will consist of two main components:
- A structured curriculum designed to enhance students' data science and analytics skills for implementing analytical projects and effectively communicating their results to management and other stakeholders;
- A consulting project in which student teams will be tasked with solving a real-world problem presented by an external organization or partner, utilizing techniques and methodologies from data science and analytics. Under the supervision of the instructor, student teams will work on the assigned problem throughout the semester, communicating with the external organization/partner during the project and presenting their results periodically throughout the project. Despite being a group project, the workload will demand each student to dedicate significantly more time to the course compared to AQM courses that do not involve work with an external organization/partner.
This course satisfies the Advanced Experiential learning requirement through an extensive project involving an external organization/partner.
Prerequisites: AQM 2000 (QTM 2000 in the older curriculum)
- Program: Undergraduate
- Division: Mathematics Analytics Science and Technology
- Level: Advanced Elective (UGrad),Advanced Liberal Arts (UGrad)
- Course Number: QTM3600
- Number of Credits: 4
QTM7200 Data, Models and Decisions
2 CreditsData, Models and Decisions (DMD) - This course is concerned with identifying variation, measuring it, and managing it to make informed decisions. Topics include: numerical and graphical description of data, confidence intervals, hypothesis testing, regression, decision analysis, and simulation. Applications to Economics, Finance, Marketing, and Operations illustrate the use of these quantitative tools in applied contexts. The course utilizes spreadsheet, statistical, and simulation software.
- Program: Graduate
- Division: Mathematics Analytics Science and Technology
- Course Number: QTM7200
- Number of Credits: 2
STR7509 Decisions, Decisions, Decisions - How Managers Make Good and Bad Choices
3 CreditsMBA students are exposed to a wide variety of concepts and tools which should enable them to make intelligent decisions. However, the decision-making performance of corporate managers, most of them trained in these concepts and tools, is very uneven.
This course will seek to enable a student to understand some key factors that can influence the quality of decision making. Using case examples from both business and government, the course will build on a basic understanding of analysis and decision making to expose participants to the circumstances that can limit the effectiveness of the techniques they have learned and help them understand the challenges they will face as members of leadership teams making complex choices throughout their careers. Students will also learn about the factors involved in providing information for decision-making, and the roles that information technology plays in decision situations.
At the conclusion of the course, students will have an appreciation for the factors they will encounter in leadership roles and the methods they can employ to ensure that they contribute to the making of good decisions. Their exposure to the broad topics presented should also acquaint them with areas which may draw their interest for more intensive study in specific academic disciplines.
Prerequisites: None
- Program: Graduate
- Division: Management
- Level: Graduate Elective (Grad)
- Course Number: STR7509
- Number of Credits: 3
HSS2025 Decolonization and Revolution in the 20th Century
4 Intermediate CreditsThe 20th Century is viewed by most historians as the most violent and tempestuous century in human history. In particular, this narrative is largely dominated by the two great wars and the Cold War. However, what made those conflicts so important was not just their impact on Europe and the Western World, but how those conflicts catalyzed mass movements globally. This class examines the history of decolonization and revolution in the 20th Century, and how the world wars and the Cold War impacted processes of nationalism, independence, decolonization and revolution. Starting with the rise of Turkey and the Bolshevik revolution during the first world war, we will then analyze the independence movements that sprouted from the vestiges of the second world war, particularly those of China and India, as well as the emergence of Apartheid in South Africa. We will also explore the impact of the Cold War on revolution and decolonization, especially Vietnam and Algeria. Finally, the course will analyze how more recent revolutions, such as those in Iran and Israel /Palestine, are rooted in longer historical processes which highlight the continuing legacy of Imperialism and revolutionary resistance to imperialism in the contemporary world. The course will use a variety of books, articles, movies, and music to analyze this deep, violent, and often conflicted aspect of human history.
Prerequisites: (FCI1000 or AHS1000) and (WRT1001or RHT1000)
- Program: Undergraduate
- Division: History and Society
- Level: Intermediate Liberal Arts (UGrad)
- Course Number: HSS2025
- Number of Credits: 4
QTM 3601: Deep Learning in Business
4 advanced liberal arts credits
This course is dedicated to learning a type of artificial intelligence through building neural network models that mimic the human brain to solve complex business problems, which involves a variety of data types like text, image, sequential, etc. The course will build on analytical concepts learned from the AQM2000 (Predictive Business Analytics) course and introduce other unsupervised and self-supervised machine learning concepts in types of neural networks, natural language processes, and reinforcement learning. Each concept contains topics like model building and parameter tuning through optimization, regularization, etc. These advanced topics will be discussed in the context of practical real-world applications such as prediction, classification, image recognition, text analysis, gaming, etc. The implementation of the introduced topics will be carried out in Python programming language.
Prerequisites: AQM 2000
- Program: Undergraduate
- Division: Mathematics Analytics Science and Technology
- Level: Advanced Elective (UGrad),Advanced Liberal Arts (UGrad)
- Course Number: QTM3601
- Number of Credits: 4