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DS 100 – Introduction to Data Science
DS 100 - Introduction to Data Science

  • SEMESTER UNITS:

    1

  • PREREQUISITE:

    None

Course Description

This course challenges conventional thinking and equips students with essential skills for success in today’s dynamic world. It fosters creativity, innovation, and problem-solving through critical evaluation of paradigms. Students learn data analysis, business strategies, and tools, and develop proficiency in methodologies like the EGAD Framework and Agile principles. Cultivating programmatic thinking and problem-solving skills prepares students for success in their professional endeavors.

Course Learning Outcomes

  • Challenge conventional thinking: Critically evaluate
    existing paradigms, assumptions, and approaches to problem-solving and decision-making, fostering creativity, innovation, and alternative perspectives.
  • Recall the basic principles and foundations of data analysis, business strategy assessment, and the utilization of data tools and techniques in business contexts.
  • Employ methodologies for data solution development: Collaborate in teams, apply problem-solving techniques, and manage projects throughout the product development lifecycle using frameworks such as the EGAD Framework and Agile principles.
  • Utilize a robust toolkit for problem-solving: Apply problem-solving methodologies, structured thinking principles, and design thinking concepts to solve complex problems, approach diverse information types, cultivate reflective thinking skills, and effectively address problems.
  • Apply programmatic thinking: Analyze problems, construct algorithms, and implement logical solutions using various tools such as algorithms, operators, flowcharts, pseudocode, and conditional statements, enabling them to tackle challenges in diverse domains effectively.