Detailed Course Information

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DS 3000 - Foundations of Data Science
Introduces methods and concepts from linear algebra and probability that form a basis for modern machine learning. Emphasizes computational aspects using the Python programming language (the course assumes familiarity with Python). Students work with tensors (in NumPy) and may be tasked with implementing from scratch algorithms central to numerical linear algebra and introductory machine learning. 4.000 Credit hours 4.000 Lecture hours Levels: Undergraduate Schedule Types: Lecture Data Science Department Course Attributes: NUpath Analyzing/Using Data, NUpath Natural/Designed World, Computer&Info Sci Restrictions: Must be enrolled in one of the following Levels: Undergraduate Prerequisites: Undergraduate level CS 2510 Minimum Grade of D- or Undergraduate level DS 2500 Minimum Grade of D-

DS 3000 - Foundations of Data Science

Introduces methods and concepts from linear algebra and probability that form a basis for modern machine learning. Emphasizes computational aspects using the Python programming language (the course assumes familiarity with Python). Students work with tensors (in NumPy) and may be tasked with implementing from scratch algorithms central to numerical linear algebra and introductory machine learning.
4.000 Credit hours
4.000 Lecture hours

Levels: Undergraduate
Schedule Types: Lecture

Data Science Department

Course Attributes:
NUpath Analyzing/Using Data, NUpath Natural/Designed World, Computer&Info Sci

Restrictions:
Must be enrolled in one of the following Levels:
Undergraduate

Prerequisites:
Undergraduate level CS 2510 Minimum Grade of D- or Undergraduate level DS 2500 Minimum Grade of D-

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Detailed Course Information

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