This module is designed to introduce Executive MBA students to the world of Python programming, specifically tailored for applications in Fintech and Finance. The curriculum is structured to provide a balance between theoretical concepts and hands-on coding exercises, ensuring that students not only understand the underlying principles but also gain practical experience.
To equip students with the foundational Python programming skills necessary to analyze financial data, make informed decisions, and understand the technological advancements in the Fintech sector.
Introduction to Exploratory Data Analysis (EDA)
Importance of EDA in decision-making. Overview of common EDA techniques and objectives.
Introduction to a business or industry-related dataset. Loading and understanding the dataset using Pandas.
Handling missing values. Removing duplicates. Data transformation and feature engineering.
Analyzing basic statistics of the dataset. Creating visualizations to gain insights (bar plots, histograms, scatter plots, etc.).
Identifying patterns, trends, and correlations. Formulating business-related hypotheses based on findings.
Understanding the significance of the Pandas library in data analysis. Hands-on exercises on Pandas data structures and basic operations.
MBA students with an interest in Fintech, Finance, or Data Analysis. No prior programming experience is required.
Basic understanding of financial concepts. A laptop or computer with Python and Jupyter Notebook installed.
Interactive lectures to explain concepts. Hands-on coding exercises and assignments. Code tracing activities for intuitive understanding. Group discussions and presentations on findings.