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Lowest historical GPA first. At least 100 letter grades over the five years through the
selected term. Grades reflect past outcomes, not workload or a guaranteed result.
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31 courses
Ranked courses have at least 100 recorded letter grades.
An introductory course for non-business majors covering basic concepts, practices, and analytical methods in the market enterprise system, with a focus on accounting, finance, and business law.
Students found exams challenging, with some noting they were harder than provided preparation materials. Grading relied heavily on exams and a few response paragraphs.
Business Law covers the history of legal development, contracts, agency, sale of goods, and insurance. It describes the American legal system and applies rules on negligence, IP, and employment.
Business Analytics I develops quantitative intuition via database management, visualization, probability, and regression analysis using Excel and business cases.
Students described the exam as long and difficult, while case studies required significant time. One student noted the absence of graded homework, quizzes, or a textbook in their term.
Business Analytics II focuses on predictive and prescriptive analytics, using historical data for forecasting and decision models to identify optimal managerial actions.
Students emphasized the need to practice Excel skills before exams. One review noted that earning every point outside the final was necessary to have a good chance at an A.
High-level introduction to business concepts for non-business majors, covering management, marketing, strategy, entrepreneurship, ethics, supply chain, and international business.
Intermediate Data Analysis for Business emphasizes predictive and prescriptive analytics, using historical data to forecast outcomes and formulate optimal decision models.
Calculus-based introduction to statistical inference and modeling (regression, time series) applied to business data for decision-making under uncertainty.
Examines how firms, governments, and civil society shape free market capitalism and its tradeoffs, then applies that analysis to reimagining capitalism for prosperous societies and planetary health.
Data to Decisions explores statistical inference and data analytics tools, reviewing foundations of statistics, machine learning, and probability theory applied to business examples using Excel and R.
Economics for Managers applies economic principles to examine how firm, industry, and global market conditions affect day-to-day managerial decisions and long-term strategic planning.
Develops workplace writing, speaking, and listening skills through audience analysis, varied written genres, formal presentations, and professional research.
Past student reviews · Dominique Hacker, Amanda Kenny, Liam Kane-Grade
The course demands significantly more time than a standard 3-credit class, with multiple weekly assignments and readings. Students reported that the workload often felt like busy work that was difficult to manage alongside other classes.
Foundation course on managing business analytics consulting projects, covering client engagement, consulting tools, and traditional versus agile project management.
Consulting Skills Bootcamp introduces consulting tools and models, focusing on applying the SCQ framework to business cases and preparing persuasive presentations.
Covers data analytics technologies including extracting structured/unstructured data, using Python for web scraping and social network mining, and leveraging libraries for advanced analysis.
Human-Centered Design and Business teaches design thinking's iterative process—empathy, systems thinking, ideation, prototyping, and testing—plus balancing desirability, feasibility, and viability to bring projects to market.
Consulting Project Capstone synthesizes program material through an applied consulting project where students identify business challenges, apply analytic methods, develop recommendations, and communicate findings.
Some students described the class as easy and noted that Professor Karunakaran’s lectures were not test-heavy, though others found the material challenging to follow.
Introduction to machine learning and AI models for business analytics, covering supervised learning, additive models, CARTs, bagging/boosting, deep learning, and unsupervised techniques like clustering.
Explores using AI to automate business processes, covering common use cases, popular tools, and providing hands-on opportunities to implement automation solutions.
Business Statistics Using Python is a compact primer covering probability, estimation, inference, correlation, and regression for data-driven business analysis.
Data Visualization & Cloud Technologies provides experience in data visualization and cloud technologies to support business analytics, including building scalable data warehouses and deploying machine learning models.
Prepares students for ethical challenges outside academia by focusing on the role of personal values in decision making, from personal to professional contexts.
Current Topics in Business Analytics and Artificial Intelligence covers emerging industry topics via applied learning experiences including case studies, industry meetings, and workshops.
Case Interview Analysis teaches students to prepare for case interviews, analyze problems with limited information, consider alternatives, and present solutions effectively using systematic approaches and analytical frameworks.
InterCultural Communication in Business develops awareness of cultural influences on business, focusing on attitudes toward work, time, and possessions across global social and religious contexts.
The midterm relied heavily on personal experiences, which could be difficult for students with limited background. Additionally, grades took a long time to return, and the provided feedback was often not very helpful.