Welcome to the Fall 2024 semester of AMAT 502 at UAlbany!
Modern Computing for Mathematicians (AMAT 502) is meant to be the core requirement of the Data Science Masters program here at UAlbany. This course will provide an introduction to programming for students who have never coded before as well as a refresher for more experienced programmers. The focus of the course is on getting to machine learning and data science applications as quickly as possible, so you may want to supplement the foundations of this class with additional practice.
At a high-level, this course has three parts:
- 8 lectures on Programming Fundamentals in Python
- 4 lectures on Numpy, SciPy and Statistics
- 11 lectures on the machine learning using Pandas and Scikit-Learn as well as its conceptual underpinnings. The remaining time will be for group projects and presentations. See this semester's website for more info.
Each of these lectures have been recorded and are available on the AMAT 502 YouTube Channel. Please subscribe!
It is your responsibility to watch the lectures before class so that we can work on the corresponding LIVE notebook during class!
The target audience for this class are data science masters students, with an undergraduate background that includes calculus, linear algebra, probability and statistics. However, I will provide a refresher of some of these topics as we move through the course.
The lecture notebooks provide a self-contained reference for the course, but supplementing with additional reading from these sources may be helpful.
- Introduction to Computation and Programming Using Python by John V. Guttag, 2nd ed (and now in its 3rd edition)
- Python Data Science Handbook by Jake VanderPlas. You can access this book for free on Github
We will cover the first eight chapters of Guttag and some of the later chapters as well. Chapter 5 of VanderPlas will guide much of our machine learning material.