Data and Models Courses

A Note from Dr. Keck: New Data and Models Curriculum

One of the most exciting developments at the school this year is the roll out of our new Data and Models three course sequence. 

The objective is to present an integrated foundation for methods supporting designs, decisions, and strategies under uncertainty, broadly defined, in situations where data exists, or can be gathered or developed. 

The curriculum constraints had included introductory probability and statistics as an obvious component or prerequisite, yet our students have been required to take four or more different prob/ stats courses between their freshman and senior years! Another constraint, as you well know, was that we can’t just add courses to a student’s plan of study. Considerable effort by the director and faculty yielded a solution that optimally addressed the objective and the constraints. 

Last fall we introduced Data and Models I:  Foundations of Data Analytics which provides credit for STAT 380.  It was presented as a foundation for subsequent topics that included machine learning, randomness, time dependence, and simulation. The course stressed programming, simulating, and visualizing the principles of probability and statistical inference. The first few problem sets, for example, included a Monte Carlo simulation, a Markov model, Brownian motion, simulation of the Monte Hall problem and Bayesian probability updating. This year the course was taken by our sophomores and juniors, but next year this is a first semester sophomore course. 

This current spring semester those students are taking the second course in the sequence, Data and Models II: Foundations of Data Science, which provides a strong foundation, as well as problem solving skills in data science and machine learning. The methods of supervised and unsupervised, as well as classification and regression learning are covered. This course provides elective credit in computer science. The faculty were impressed to see sophomores doing neural network predictions in the first problem set and participate in a Kaggle competition in the third problem set! The latter weeks of the course allow the students to pursue their own specializations such as big data, cloud deployment, or tools such as TensorFlow and Tableau. 

The third course, Data and Models III: Foundations of Management Science, will be offered for the first time next year. This course will address time dependent methods, optimization, and simulations including Monte Carlo and agent based. Since this course provides students with required credits for business, the application focus will include forecasting, scheduling, resource allocation, and simulation of business operations and human-based systems including organizations and markets. 

We look forward to connecting and leveraging these topics with other school courses.   We also look forward to students being able to take more advanced electives in these areas during their junior and senior years.  And of course, we look forward to pursing increasingly high value Design Studio projects that leverage the methods and insights gained.  

We look forward to your feedback and support!