Auburn University
Relevant Coursework for Marketing
MKTG 3310: Principles of Marketing
The study of functions, institutions, and basic problems in marketing of goods and services in a global economy. In this course, I applied the marketing theory to real world contexts, learned about the current events of marketing, and to get a basic grasp and understanding of marketing concepts and practices.
MKTG 4390: Personal Selling
The study of the selling strategy as an interdisciplinary business activity.In this course, I gained better knowledge on which sales methods/techniques work, help determine which type of sales career fits me best, and learn how to sell myself and determine short and long term career goals.
MKTG 4430: Business to Business Marketing
The study of marketing strategy and applications for business-to-business companies and markets. In this course, I learned that business marketers serve the largest market of all: the dollar volume of transactions in the industrial or business market significantly exceeds that of the ultimate consumer market. The the major points that were stressed in this course were : 1) Understand how B2B marketing works and how it is similar and different to B2C marketing, 2) How selling to B2B companies differs from selling to B2C firms, 3) Understand how to plan, develop, execute and measure the impact of B2B marketing strategies.
MKTG 4400: International Marketing
This course is designed to provide students with a basic understanding of marketing concepts and practices applied in an international context. The focus of this course is similarities and differences when practicing marketing in international contexts.
MKTG 4360: Marketing Research and Analytics
The primary objective of the course is to help students learn how to acquire information that is useful in making responsible marketing decisions. The course will provide students with a broad understanding of responsible marketing research procedures. In this regard, students will examine the need for marketing research and basic steps in the marketing research process – i.e., planning the study, collecting and analyzing the data, and utilizing the resulting information to make responsible managerial decisions. Specific topics to be discussed include problem formulation, research design, identification of useful information sources, concept measurement, questionnaire design, sampling, data collection, data analysis and hypothesis testing with EXCEL, and report preparation. Theoretical discussion of these topics will also address their applicability to practical marketing research.
Relevant Coursework for Analytics
BUAL 2650: Business Analytics II
The second course in quantitative analysis in business including statistical inference, classification analysis, predictive modeling, forecasting, introduction to data mining. In this course, I learned how to use model-based estimation and prediction methods with business applications, understand probability distributions common in business and the relationships between sampling, probability, and uncertainty in business decision making, and learn the importance of business sampling methods.
BUAL 5600: Predictive Modeling I
The study of basic data mining techniques including neural networks, decision trees, clustering algorithms, linear programs, text and web mining in business setting. In this course, I learned how to use predictive models and R software technology to solve real problems in business analytics, examine fitted models and evaluate their predictive and explanatory power, and understand which modeling methods are appropriate in various situations.
BUAL 5650: Big Data I
The study of managing, governing, extracting, merging, and preparing large data sets for analysis. In this course, I learned the strategic use of resultant datasets, data quality, governance issues, and security, a brief introduction to programming for data analysis, and an understanding of the management of data for use in organizations.
BUAL 5610: Predictive Modeling II
This course aims to go beyond the traditional regression methods and to provide a much applied overview to those modern predictive methods, such as Decision Trees, Random Forest, Bagging and Boosting, Neural Network and Deep Learning, and Support Vector Machines. We will cover these approaches in the context of Marketing, Finance and other important business decisions.
At the end of this course, you should have a basic understanding of how these methods work and are able to apply them in real business situations.
BUAL 5660: Big Data II
This course is designed as an introductory course on data management, analysis, and interpretation, particularly with regard to the term “Big Data.” To fully understand what all the fuss is about, one must first understand data as a grossly underutilized business asset. This class goes beyond the topics covered in Big Data I and advance new topics in big data management, with emphasis on loading and cleansing the data for analysis.