Course Description
An introduction to concepts in scientific programming and data science using the Python language. Students are given hands-on opportunities to learn techniques applicable to quantitative analyses across a broad range of fields. Core programming concepts are taught in tandem with real-world applications.
Athena Title
Informatics and Data Analytics
Equivalent Courses
Not open to students with credit in CSCI 1360E
Prerequisite
MATH 1113 or MATH 1113E
Semester Course Offered
Not offered on a regular basis.
Grading System
A - F (Traditional)
Course Objectives
Provides an introduction to concepts in scientific programming and data science using the Python language. Upon the conclusion of this course, students should be able to formulate solutions to problems in a broad range of fields in terms of their inputs and outputs (functional programming), repeated operations (loops), branching operations (conditionals), different methods of organizing data (data structures), how to implement an optimal problem-solving strategy (algorithm design),and how to visualize and interpret results.
Topical Outline
Introduction to data science Functional programming Loops, conditionals, variables, functions, control flow Data structure (lists, arrays, dictionaries, matrices) Vectorized programming Linear algebra and statistics Data preparation and preprocessing Importing and creating external packages Data plotting and visualization
General Education Core
CORE III: Quantitative ReasoningSyllabus