Python Fundamentals for Business Analytics
Master Python programming for business analytics through hands-on exercises, from basic syntax to data manipulation with NumPy and real-world applications.
Master Python programming for business analytics through hands-on exercises, from basic syntax to data manipulation with NumPy and real-world applications.
This introductory course provides a comprehensive foundation in Python programming specifically tailored for business analytics applications. Designed for students with no prior programming experience, the curriculum begins by establishing core programming concepts before progressing to more advanced Python techniques. Students start by mastering essential components including variables, relational and boolean operators, control statements, and input/output operations. The course then advances to programming with functions, lists, and tuples. In the final phase, students learn to leverage the powerful NumPy library, a fundamental tool for data manipulation and analysis in business contexts. Throughout the course, real-world business analytics examples and interactive coding exercises reinforce learning and demonstrate practical applications. Students code alongside the course materials, developing hands-on experience that bridges theory and practice. By completion, participants will have developed a strong understanding of programming principles, gained proficiency in Python syntax, and acquired the skills to apply Python functions to basic analytical problems—providing a solid foundation for more advanced business analytics techniques.
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What you'll learn
Install and use the Anaconda distribution of Python through Jupyter notebooks Understand and implement variables and common Python data types including numeric, string, boolean, and collections Create expressions using variables with relational and boolean operators Implement program flow control using conditional statements and loops Read data from and write data to text files for business data processing Utilize the NumPy library for efficient numerical computing and data analysis Implement and test algorithms in Python to solve business problems Apply Python functions to basic analytical challenges in business contexts
Skills you'll gain
This course includes:
PreRecorded video
Graded assessments, coding exercises
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Limited Access access
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Module Description
This comprehensive course introduces Python programming fundamentals with a specific focus on business analytics applications. The curriculum is designed for beginners with no prior programming experience and follows a structured approach to building coding skills. Students begin by learning to set up their development environment using the Anaconda distribution and Jupyter notebooks. The course then covers core programming concepts including variables, data types (float, integer, string, boolean, lists, and tuples), expressions with relational and boolean operators, and program flow control using conditional statements and loops. Students learn essential file operations for reading from and writing to text files, a crucial skill for working with business data. The curriculum extends to utilizing important analytical libraries, particularly NumPy, which provides powerful tools for numerical computing and data manipulation. Throughout the course, students develop algorithm implementation and testing skills through interactive coding exercises and real-world business examples. The hands-on approach ensures students not only understand Python syntax but can apply it effectively to solve business analytics problems.
Fee Structure
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Instructor
Catherine Ridings: A Leader in Virtual Community Research
Dr. Catherine Ridings is a Professor Emeritus in the College of Business at Lehigh University, where she dedicated 23 years to academia. She served as the Director of the Undergraduate Business Information Systems program from 2006 to 2013 and held the position of interim department chair for Decision and Technology Analytics. Dr. Ridings has taught various courses, including Java programming, Artificial Intelligence, and Database Management. Her primary research focuses on virtual communities, exploring aspects such as social networks, trust, knowledge management, and electronic commerce. She has published extensively in reputable journals like the Journal of Management Information Systems and received accolades for her dissertation on trust in virtual communities, which won the Decision Sciences Institute's 2001 Elwood S. Buffa Doctoral Dissertation Award. Her contributions to the field have been recognized with Lehigh University's Robert and Christine Staub Faculty Excellence Award in 2020 and the Deming Lewis Faculty Award in 2023. Dr. Ridings holds a Ph.D. in Decision Sciences (Management Information Systems) from Drexel University, an MBA from Drexel University in Management Information Systems, and a BS/BA from Villanova University in Computer Science and Arts & Sciences Honors Program.
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