Applied Data Science (324-DL-20)

Instructors

Sunilkumar N Kakade

Meeting Info

Online: TBA

Overview of class

This course introduces data science concepts, techniques, and tools with an emphasis on building practical business applications. Students will gain the ability to decompose a business problem into actionable data science tasks that include exploratory data analysis, data visualization, data preprocessing and building predictive models using right algorithms. Using Python, students will implement supervised and unsupervised machine learning methods. The students will be exposed to a variety of machine learning algorithms including regression, classification, clustering, dimensionality reduction, and neural networks. This course takes a hands-on approach to prepare students to use data science with the focus on building data products for various industries. This course is conducted completely online. A technology fee will be added to tuition.

May not be audited or taken P/N.

This course was formerly CIS 395-CN Topics: Principles of Data Science.

Registration Requirements

Prerequisite: CIS 323 Introduction to Python or equivalent. Enrollment restricted to students who have completed CIS 323. Instructor consent (permission number) is required for all other students.

Class Materials (Required)

Materials available through Canvas/course reserves.

Class Attributes

Asynchronous:Remote class-no scheduled mtg time