BUS 41204: Machine Learning
machine-learningmba-educationcourse-syllabus
Abstraction: Chicago Booth inaugural MBA machine learning course 2015
Key points:
- Claimed to be the first MBA machine learning course at any leading US or international business school (Fall 2015)
- Covers supervised learning: Decision Trees, kNN, Boosting, Random Forests, Deep Neural Networks, Naive Bayes, SVMs
- Covers unsupervised learning: Clustering, Collaborative Filtering, PGMs, Dimensionality Reduction
- Taught by Mladen Kolar and Robert E. McCulloch; R is the primary computing language, Python supported
- Grading: 20% homework (8 assignments, top 7 count), 40% take-home midterm, 40% final project
- No required textbook; recommends ISL, ESL, and Murphy's ML: A Probabilistic Perspective
Connections: Chicago Booth · Mladen Kolar · Machine Learning · Supervised Learning · Unsupervised Learning
Source: http://chicagoboothml.github.io/MachineLearning_Fall2015/