Document Type

Syllabus

Publication Date

Spring 2024

Course Description

An intermediate course in business analytics for students who have completed a statistics course. Develops data management, programming, and analytical skills to guide business decision-making. May cover tools such as Python, R, Julia, and Tableau and topics such as LASSO, random forests, and spreadsheet models.

Student Outcomes

1) use Python (NumPy, pandas) to efficiently clean, preprocess, and manipulate large datasets.2) perform comprehensive Exploratory Data Analysis (EDA) to gain insights from data, identify patterns, and detect outliers. 3) create meaningful data visualizations using tools like Matplotlib to effectively communicate findings. 4) process, and analyze raw real-world data into actionable insights, extracting meaningful information for decision-making. 5) engage in critical thinking and ethical discussions surrounding data privacy, bias, and transparency. 6) effectively work in teams to tackle complex business analytics projects, integrating various programming languages and analytical techniques.

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