Computational tools and methods are a cornerstone of the data scientist's toolbox, useful in a variety of applications and disciplines. This course builds on introductory data science and computer programming skills to equip students with several of these tools and methods. Computational methods for gathering and storing data via web APIs or web scraping or other formats; data pre-processing methods useful in data science algorithms; using version control and other tools to implement reproducible data science workflows; using web tools to communicate data science results and build data science products; creating, distributing, and accessing open-source data science software libraries. This course assumes prerequisite experience in computer programming, but does not require any additional knowledge or prior experience with any of the tools or methods covered.
Computational tools and methods are a cornerstone of the data scientist's toolbox, useful in a variety of applications and disciplines. This course builds on introductory data science and computer programming skills to equip students with several of these tools and methods. Computational methods for gathering and storing data via web APIs or web scraping or other formats; data pre-processing methods useful in data science algorithms; using version control and other tools to implement reproducible data science workflows; using web tools to communicate data science results and build data science products; creating, distributing, and accessing open-source data science software libraries. This course assumes prerequisite experience in computer programming, but does not require any additional knowledge or prior experience with any of the tools or methods covered.
