Babson College has only business majors, and this without a doubt impacts both what we cover and how we cover it. Almost all of my examples are from business and industry, and I present some material more like case studies than a traditional lecture. I think that inquiry-based learning is especially important with a non-mathematician audience, and I've been working hard to integrate more IBL material into my courses.

Data Analytics

I've taught data analytics at both the undergraduate and graduate levels using a number of different computational platforms. While these courses all have different flavors, we do cover bread and butter classifiers like KNN, logistic regression, and classification trees and unsupervised learning methods like k-means and association rules in every course. A subset of the detailed slides I use to teach analytics in R to our undergraduates can be found here. If you'd like a sample of quizzes, exams, or case reports, just contact me.

I've taught data analytics at both the undergraduate and graduate levels using a number of different computational platforms. While these courses all have different flavors, we do cover bread and butter classifiers like KNN, logistic regression, and classification trees and unsupervised learning methods like k-means and association rules in every course. A subset of the detailed slides I use to teach analytics in R to our undergraduates can be found here. If you'd like a sample of quizzes, exams, or case reports, just contact me.

Cryptography and Coding Theory

Babson's Teaching Innovation Fund was kind enough to sponsor my writing a course pack, including lecture notes, problems, solutions, and teaching notes, for a cryptography course. Some notable features of the course include:

This document is offered free of charge under the Creative Commons license. Feel free to edit, redistribute, remix, etc. as you see fit. If you end up using part or all of these notes in a course, I'd appreciate your letting me know.

Below is a short sample which includes the table of contents. You can also download the full document and the LaTeX source.

Babson's Teaching Innovation Fund was kind enough to sponsor my writing a course pack, including lecture notes, problems, solutions, and teaching notes, for a cryptography course. Some notable features of the course include:

- Guided implementation of classic cryptosystems (encryption, decryption, and cryptanalysis) in MATLAB
- Ethics articles and discussion questions
- Studio problems and solutions for all lessons
- Teaching notes discussing major themes, common student misunderstandings, and directions for further development

This document is offered free of charge under the Creative Commons license. Feel free to edit, redistribute, remix, etc. as you see fit. If you end up using part or all of these notes in a course, I'd appreciate your letting me know.

Below is a short sample which includes the table of contents. You can also download the full document and the LaTeX source.

## Linear Algebra and Dynamical Systems

We cover most of the traditional linear algebraic material, but the motivation and ordering is different than many courses. We use multi-industry consumption models to motivate matrix arithmetic, the Leontief input-output model to bring out the matrix inverse, the Leontief price equation to develop sensitivity analysis, a dynamical systems model of an airline customer loyalty program to discover eigenthings, a revisitation of linear and multiple regression to see orthogonality and projections, and consumer behavior prediction to motivate singular value decomposition and principal component analysis. We cover things roughly in this order. If you're interested, you can check out the current syllabus and course notes. (If you end up using anything from the course notes, let me know how it turns out so I can use your feedback in the next iteration.)

## Applied Calculus and Quantitative Methods

This course's aim is primarily to get students thinking about applied mathematics as a tool for use in real world situations. We cover linear models, differential calculus in the context of marginal analysis, linear programming, basic finance, and a little bit of integral calculus.

As incoming first-years, many students have the preconception that "using mathematics" means completing a worksheet full of derivatives. I use technology (calculators, WolframAlpha, Excel, Solver, etc.) to offload the mindless work and ask them to focus on thinking critically about how best to approach a given problem. The typical assessment is a take home exam on which students may collaborate and/or use any outside resource they'd like. Students then complete an oral exam individually related to the material on the take home portion. This allows me to ask more interesting, unstructured, and realistic questions, and allows the students to practice working, learning, and teaching. If you're interested, you can check out the current syllabus and an example of a take-home final.

As incoming first-years, many students have the preconception that "using mathematics" means completing a worksheet full of derivatives. I use technology (calculators, WolframAlpha, Excel, Solver, etc.) to offload the mindless work and ask them to focus on thinking critically about how best to approach a given problem. The typical assessment is a take home exam on which students may collaborate and/or use any outside resource they'd like. Students then complete an oral exam individually related to the material on the take home portion. This allows me to ask more interesting, unstructured, and realistic questions, and allows the students to practice working, learning, and teaching. If you're interested, you can check out the current syllabus and an example of a take-home final.