Information Systems

• QST IS 999: Directed Study: Info Systems
  Graduate Prerequisites: consent of instructor and the department chair - PhD-level directed study in Management Information Systems. 1, 2, or 3 cr. Application available on the Graduate Center website.
• QST MK 842: Machine Learning for Business Analytics
  Graduate Prerequisites: (QSTMK723 OR QSTMK724) - This course introduces students to the foundational machine learning techniques that are transforming the way we do business. Machine learning relies on interdisciplinary techniques from statistics, linear algebra, and optimization to detect structure in large volumes of data and solve prediction problems. Students will gain a theoretical understanding of why the algorithms work, when they fail, and how they create value. They will also gain hands-on experience training machine learning models in Python and deriving insights and making predictions from real-world data. Prior programming experience (or IS833/IS834) is strongly recommended. Note: The course was previously offered under the title "Digital Marketing Analytics," but does not overlap with MK876; students may take both courses for credit.
• QST QM 877: Intro to Python Bootcamp
  In this Bootcamp, students will learn the most essential aspects of Python programming. The topics are tailored toward data analysis; no prior programming experience is required. We will cover variables, data types and data structures, DataFrames, conditionals, loops, and functions. We will also cover reading and writing raw files and the core APIs in analysis and visualization. With the basics under our belt, we will complement it with some of the most popular libraries for data analysis in Python, such as Pandas and Numpy for data manipulation, Matplotlib and Seaborn for visualization, and Jupyter Notebook for reporting. These packages will facilitate workflow and enhance the basic Python functionalities. Using them, one can effortlessly clean up a dataset, create elaborate plots, analyze and summarize the data, and produce presentable reports. During this module, you solidify your new skills by applying the concepts you have learned to analyze several datasets. You will have a chance to live-code during the sessions and troubleshoot your code with your classmates and the instructor. You will walk out of this Bootcamp with newly-forged Python coding skills, knowledge of several of the most important data science libraries and tools, and the resources for learning more. 1.5 cr
• QST QM 878: Deep Learning with Python Bootcamp
  Graduate Prerequisites: QM877, IS833, IS834 or instructor permission - In this bootcamp, students will learn the most essential aspects of machine learning, and in particular, deep learning in Python. Prior programming experience in Python is required. We will cover some standard machine learning algorithms and solve business problems using tabular, time-series, and image data using deep learning algorithms. During this module, students solidify their new skills by applying the concepts they have learned to analyze several datasets. They will have a chance to live-code during the sessions and troubleshoot their code with their classmates and the instructor. 1.5 cr.