Course Description

Scripting for the data analysis pipeline. Acquiring, accessing and transforming data In the forms of structured, semi- structured and unstructured data.

Additional Course Description

The goal of this class is to teach students the tools and skills of scripting needed to solve problems of accessing and preparing data in a variety of formats and situations, sometimes known as data wrangling. The scripting learned will provide the skills needed to form data science pipelines, from acquiring and cleaning data to accessing data and transforming data for analysis or visualization.

Credit(s)

3.0

Professor of Record

Carlos Caicedo Bastidas

Audience

Students of the Master’s Degree program on Information Management and the Master’s Degree program on Applied Data Science are the primary audience for this course. Students in other graduate degree programs may enroll with permission of theinstructor.

Learning Objectives

After taking this course, students will be able to:

Write scripts to access and amass information from files of structured data, access files in semi-structured data, and to define and find patterns in unstructured data.
Prepare and transform data to produce data summaries, lists, and networks.
Analyze and solve data access problems for the three types of data and to find and deploy appropriate software packages that can be integrated into the problem solution.
Frame real world data questions and show how they can be answered with data.

Course Syllabi

IST 652 Fall 2021 Semester Syllabus- Carlos Caicedo Bastidas

IST 652 Quarter Term Syllabus - Deborah Landowski

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