This set of modules establishes foundational knowledge for the OpenDS4All curriculum.
Initially we include an overview of computer architecture, appropriate as a prerequisite to discussing algorithmic performance.
For those students unfamiliar with probability theory and very basic statistical notions, additional material on probability distributions and summary statistics are added to help them better understand the content of the other lectures. Also, for students new to programming, additional material on working with data, such as reading in a file, reviewing the data, querying data and sorting data are added to facilitate a better understanding of the material with a higher difficulty level in the data wrangling and integration category.
- Overview / review of computer architecture basics, including CPUs and memory hierarchy: HOW-COMPUTERS-WORK-cpu-memory-ssd-basic slides.
- Graph theory basics, including network centrality and breadth-first search: GRAPH-THEORY-basic slides.
- Summary statistics and probability distributions: DATA-EXPLORATION-Summary-Statistics-intro slides
- Getting started with data: GETTING-STARTED-Data-Load-Query-Sort-intro slides
- Initial release, Susan Davidson and Zachary Ives, University of Pennsylvania, February 2020.
- Supporting introductory material, Xumin Liu, Rochester Institute of Technology, August 2022.