Course Description
This course introduces students to foundational skills in data analytics, with a focus on mathematical foundations. Students will explore topics that form the backbone of modern data analytics such as machine learning, data mining, artificial intelligence and visualization. Tools for statistics will be introduced to students for how to go from raw data to a deeper understanding of the patterns and structures within the data, to support making predictions and decision making.
Books Required:
● Jiawei Han, Michelle Kanber, Jian Pei. Data Mining: Concepts and Techniques. 4th edition, Morgan Kaufman Publishers, 2023.
● Sharda, Delen, Turban. Analytics, Data Science & Artificial Intelligence, Systems for Decision Support. Pearson Global Edition, 11th edition, 2021
● Lecture Slides
Programming Language: R
R is a programming language that runs computations, while RStudio is an integrated development environment (IDE) that provides an interface by adding many convenient features and tools. So just as the way of having access to a speedometer, rear view mirrors, and a navigation system makes driving much easier, using RStudio’s interface makes using R much easier as well. Please read the tutorial getting started with Data in R with the installation instructions for Windows and Mac operating systems.
R is a programming language that runs computations, while RStudio is an integrated development environment (IDE) that provides an interface by adding many convenient features and tools. So just as the way of having access to a speedometer, rear view mirrors, and a navigation system makes driving much easier, using RStudio’s interface makes using R much easier as well. Please read the tutorial getting started with Data in R with the installation instructions for Windows and Mac operating systems.