Course Description
Provides 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 analysis 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 1360
Non-Traditional Format
This course will be taught 95% or more online. The course content is delivered fully online; students will utilize the features of eLC and GitHub to access a variety of experiences involving text and multimedia presentations of content, intensive practice, online discussion, and expert support. Quizzes and proctored exams will also be offered through a combination of online and in-person proctored sessions, which may have proctoring fees associated with them.
Prerequisite
MATH 1113 or MATH 1113E
Semester Course Offered
Offered summer semester every year.
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 structures (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