COMPUTER & DATA SCIENCE

Become a Data Guru

The major in Computer and Data Science prepares students to apply an understanding of computer platforms and systems, human-machine interactions, and IT operations, as well as gain quantitative proficiency in data gathering, data analytics, and insight generation to tackle organizational and societal problems effectively and creatively.

Providing students with solid foundation in research methods, mathematics for statistics, visualization techniques, and the latest methods in machine learning and big data wrangling, this major is for analytically-inclined students who are interested in starting careers as IT product and project managers, researchers, data scientists, or simply in applying quantitative learning to solve real world problems in any career setting. The major is at its core interdisciplinary in the fact that it combines courses from computer science, social science, statistics, and business to prepare students to enter a technology-intensive and data-rich world in need of creative and critical thinking.

This major lays the foundations of learning programming languages such as R, Python, and SQL while students expand their potential to make new and exciting contributions, communicate their results, and tell stories with data that are convincing to experts and non-experts alike.

Required and Elective Courses

required for major

electives towards the major

Learning Outcomes

NewU Students majoring in Computer & Data Science will graduate being able to:

  • Apply scientific reasoning in exploring social phenomena
  • Be able to analyze data, draw conclusions, and present results to non-experts
  • Present information in the most clear, concise, and appealing way
  • Begin using a programming language such as R or Python
  • Understand IT architecture structures and management information systems
  • Begin using SQL to retrieve and manipulate data
  • Learn how to collect data, use APIs, scrape the web, and wrangle big data
  • Learn machine learning techniques, including supervised and unsupervised learning
  • Think creatively and critically about how technologies affect human perceptions, memory, work, relationships, and physical environments
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