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.

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Athena Title

Informatics and Data Analytics

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Equivalent Courses

Not open to students with credit in CSCI 1360E

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Prerequisite

MATH 1113 or MATH 1113E

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Semester Course Offered

Not offered on a regular basis.

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Grading System

A - F (Traditional)

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Student learning Outcomes

• Frame scientific experiments in terms of their inputs and outputs.
• Formulate algorithms in terms of conditionals, loops, functions, return values, data structures, and existing Python APIs.
• Write a program or package to implement automated analysis of data.
• Process data of varying types, such as text or images.
• Render appropriate visualizations of analysis results, and interpret these visualizations.

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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

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General Education Core

CORE III: Quantitative Reasoning

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