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MATH 211 Introduction to Data Science

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Course Description

Introduction to the core concepts of data science, emphasizing inferential thinking, computational thinking, and real-world relevance. Topics include statistical methods such as descriptive statistics, probability, hypothesis testing, confidence intervals, correlation and regression, and introductory machine learning. Computer programming is integrated with data analysis across multiple disciplines while considering the social issues surrounding data analysis such as privacy and design.

Units: 4
Degree Credit
Letter Grade Only
  • Lecture hours/semester: 48-54
  • Lab hours/semester: 48-54
  • Homework hours/semester: 96-108
  • Total Student Learning hours/semester: 192-216
Prerequisites: Intermediate Algebra or equivalent or pre-statistics or placement by college approved multiple measures.
Corequisites: None
AA/AS Degree Requirements: Area 2
Transfer Credit: CSU, UC, (Cal-GETC Area 2)