GPA and percentages are weighted by recorded letter grades. UW
comparisons use the same terms. Cross-listed courses count once within
this department and once across UW; department totals should not be
added together. Grade counts are not unique students. Offering counts
reflect captured records, not a complete historical schedule.
Spring 2027
Recorded this term
4747courses with offerings
4747instructors recorded
Grades have not been recorded for this term. Historical results remain
in the overview above.
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.
Advanced Bayesian statistics course covering theory, methods, and computational procedures for data analysis, including MCMC and variational inference.
Foundational Skills for Business Analysis builds business analysis skills using Excel, covering data construction, manipulation, summarization, analysis, and presentation.
Intermediate Data Analysis for Business emphasizes predictive and prescriptive analytics, using historical data to forecast outcomes and formulate optimal decision models.
A lab course where students address business problems using AI as a simulated client and practical tool, gaining skills in consulting, project management, and applied AI.
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.
The Business of Health Care covers the US health care sector from an economic perspective, focusing on businesses and services. It analyzes stakeholder incentives and government policies.
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.
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.
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.
High-level introduction to business concepts for non-business majors, covering management, marketing, strategy, entrepreneurship, ethics, supply chain, and international business.
Calculus-based introduction to statistical inference and modeling (regression, time series) applied to business data for decision-making under uncertainty.
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.
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.
A capstone course where students apply strategic frameworks to company-sponsored projects, developing skills in problem analysis, project management, communication, and leadership while navigating real-world ambiguity.
Professional Experience in Business is an internship allowing students to augment their business education and gain professional experience in their major through related work experience.
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.
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.
An introduction to foundational AI concepts and their applications in business, covering how AI works, its impact on society, and ethical considerations.
Deep dive into the strategic, operational, organizational, and cultural implications of applying AI to the business enterprise, focusing on leadership dynamics.
Explores AI's impact on management, business strategy, innovation, and the future of work, focusing on organizational transformation, leadership, competition, governance, and decision-making.
Prepares students for ethical challenges outside academia by focusing on the role of personal values in decision making, from personal to professional contexts.
Role of Business in Society explores critical thinking, communication, and managerial skills for developing ethical organizations, including ethical dilemmas and personal beliefs.
Corporate Governance and Board Membership explores the roles of Management and Directors in protecting stakeholder interests, analyzing governance environments and their impact on organizational success.