Master of Science in Business Analytics Curriculum
Fall 2019/Spring 2020
Maryland Smith’s curriculum is interactive, data-focused and adjusts to reflect the trends of the modern business world. The courses you’ll take are taught by knowledgeable scholars and experts with years of experience leading others in their field.
Database Management Systems
3 credits | BUDT 758Y
3 credits | BUDT 758P
What makes a decision difficult? Usually, the answer is that the decision requires us to spend scarce resources. A “resource” is any asset that can be leveraged to achieve business objectives: time, money, staff, trucks, computer cores, and research effort can all be viewed as resources. When you decide to spend your resource on something (e.g., investing into a research project, or accepting a delivery job), there is less of the resource that can be spent on something else. You thus have to think carefully about the tradeoffs involved in allocating resources to one objective as opposed to another.
This class develops a quantitative framework for studying resource allocation problems. Resource allocation problems arise in many industries and areas such as transportation, electronics, advertising, finance, and health care. The specifics of each problem are very different. Nonetheless, all resource allocation problems, in all of these areas, have common elements that behave in exactly the same way. We will develop an abstract modeling language that emphasizes these common elements, so that you will be able to write down any resource allocation problem on paper and then apply standard tools (such as Microsoft Excel) to obtain solutions.
Data, Models and Decisions
3 credits | BUDT 758Q
Data Mining and Predictive Analytics
3 credits | BUDT 758T
In business magazines, on TV, and in board rooms, “big data” and “data analytics” are now hot topics. Vast quantities of data are being generated these days, including new types of data such as web traffic, social network data, and reviews and comments on websites. This data is a valuable resource that, when used correctly, can create a competitive edge for companies by improving the quality of decision making. Recent advances in computing hardware and software have made the application of advanced analytical methods much easier. This course takes advantage of these developments to introduce data analytics to those interested in developing expertise in datadriven decision making.
The course is intended to provide an introduction to the tools and techniques of data mining & machine learning that are central to business analytics, with particular emphasis on classification and prediction. The focus will be on business applications and examples from Marketing, Finance, Healthcare, and Operations will be used to illustrate the breadth of applications.
Data Processing and Analysis in Python
3 credits | BUDT 758X
This course provides an introduction to the Python programming language for the purpose of processing, analyzing, and visualizing data. In addition, students will be introduced to developing basic regression, optimization, and simulation models in Python, using highly popular packages. Course emphasis is on mastering basic Python functionality and developing intermediate to advanced skills in working with data, through instruction and active learning.
Big Data and Artificial Intelligence for Business
3 credits | BUDT 758B
Big data represents unprecedented opportunities for companies to generate insights and create wealth. Huge amount of data is being generated. At the same time, much of the big data is unstructured, in real time and only loosely connected. It defies the traditional ways of managing databases. This creates challenges even to tech-savvy companies on how to leverage big data to gain competitive advantages. Challenges and opportunities coexist. To extract the great value from the data, we should be equipped with advanced techniques. Artificial Intelligence (AI) is penetrating our daily routines deeply, and shows great promise in exciting areas such as healthcare and autonomous driving cars.
This course uses a hands-on, learning-by-doing approach to understanding the concepts behind Big Data and AI, the strategic drivers of these technologies and the value propositions that they provide to industries. In addition, the course will also serve as an introduction to some of the key technologies within this ecosystem, such as Hadoop, AWS, Pig, Hive, Amazon Web Services and Spark. Examples of AI using Deep Learning will be conducted in class. The focus is on creating awareness of the technologies, allowing some level of familiarity with them through hands-on exercises and projects, and enabling strategic thinking around the use of these technologies in business.
2 credits | BUDT 758V
Google Analytics Online Challenge
3 credits | BUDT 758F
Price Optimization and Revenue Management
3 credits | BUDT 758L
1 credit | BUDT 758A
3 credits| BUDT 758W