# Reorganization and additions to Applied Math and Computer Science introductory courses

As of 8-24-2016

**Introduction to programming courses**

For a while now, we have taught the introductory programming course **CS 1 **in python and aimed at it providing students and practical introduction to programming methods. This course is taken (or passed out of) by nearly all undergraduates so you're hopefully aware of it. **CS 2** is the second part in the introduction to programming methods, and transitions students to C++ in addition to covering more complex data structures and algorithmic. It is now taken by 60%+ of undergraduates. These courses are offered yearly in the fall (CS 1) and winter (CS 2). If these courses are important for your students to take early on, I encourage you to consider checking to make sure that students can fit these courses into your option requirements without overloading given that neither is part of the core.

Beyond CS1 and CS2, students who wish to learn other programming languages are encouraged to sign up for **CS 11 (for undergrads) or CS 111 (for grads)**. These courses are 3-unit offerings that are available every term and offer tracks for nearly every popular programming language (often 10 tracks per term). These are practical courses that focus on teaching good programming practice. CS111 is new and is a useful option for advisors or graduate programs that want to require students to develop programming skills.

Additionally **ACM11** (6 units, spring) provides an introduction to Matlab and Mathematica.

**Introductory probability and statistics courses**

In the past we have only had one introductory offering in probability, ACM 116, and no regular introductory statistics offerings. However, we have reorganized our curriculum to provide a sequence of two introductory courses in both probability and statistics.

On the probability side, the **new ACM/EE 116** covers basic and intermediate probability and is appropriate for upper-level undergraduates and beginning graduate students outside of math. The **new CMS/ACM/EE 117** is a graduate level probability and stochastic processes course. Both of these courses will be offered yearly in the fall since both are required first-term courses for some graduate options on campus.

On the statistics side, the **new ACM/CS 157** provides an introduction to statistical inference and the **new ACM/CS/EE 158** provides a followup, focused mathematical statistics. 157 will be offered yearly in the winter and 158 will be offered every other year in the spring (we hope to be able to offer it yearly soon). Note that these courses connect nicely to our introductory Machine Learning offerings: **CMS/CS 155** and **CS/EE 156a. **

We know that many other areas offer courses that depend on some probability and statistics knowledge and we hope that 116 and 157 can provide this background in a consistent way, allowing other courses to move to more advanced topics more quickly.

**Introductory linear algebra**

In the past we have had only one introductory offering in linear algebra, ACM 104. We have now expanded to two yearly offerings.

The **new ACM 104** is an introductory course appropriate for upper-level undergraduates and beginning graduate students outside of math. The **new CMS/ACM 107** is an introductory graduate course appropriate for students that are already familiar with the material in ACM 104. Both will be offered yearly in the fall term since both are required first-term courses for some graduate options on campus.