Introduction to Data Analytics in Python
QST IS 833
Graduate Prerequisites: MSDT Students Only; IS717 or equivalent Python experience - This course will introduce students to programming-based tools and techniques for becoming analytically-minded managers. The course covers both a hands-on introduction to the concepts, methods and processes of business analytics as well as an introduction to the use of analytics as the basis for creating a competitive advantage. We will review variables, data types, conditionals, loops, and functions, and use these to introduce data structures, including DataFrames. 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. Throughout the final project, we will learn to extract value from data by asking the right questions and using the appropriate analytical methods and tools. These methods comprise data preprocessing, explanatory analysis, and machine learning techniques. Prior programming experience in Python is required.
SPRG 2025 Schedule
Section | Instructor | Location | Schedule | Notes |
---|---|---|---|---|
D1 | Tibert | HAR 404 | R 12:30 pm-3:15 pm |
Note that this information may change at any time. Please visit the MyBU Student Portal for the most up-to-date course information.