Course Syllabus
Course Description
The course on Introduction to Data Science provides an overview of Data Science, covering a broad selection of key challenges in and methodologies for working with big data. Topics to be covered include data collection, integration, management, modeling, analysis, visualization, prediction and informed decision making, as well as data security and data privacy. This introductory course is integrative across the core disciplines of Data Science, including databases, data warehousing, statistics, data mining, data visualization, high performance computing, cloud computing, and business intelligence. Professional skills, such as communication, presentation, and storytelling with data, will be fostered. Students will acquire a working knowledge of data science through hands-on projects and case studies in a variety of business, engineering, social sciences, or life sciences domains. Issues of ethics, leadership, and teamwork are highlighted.
(Prerequisite: a basic background in computer programming and statistics, either at the undergraduate or graduate level.)
Detailed Syllabus with Course Description, Objectives, Resources, Course Approach, Information regarding Communication, Assignments, Grading and Support can be found in the below PDF file.
Course Videos can be found on Echo360
https://canvas.wpi.edu/courses/4478/external_tools/92
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Course Summary:
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