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ECE 461P ECEĀ 461P. Data Science Principles. 4 Hours.

Examine principles of unsupervised and supervised learning; exploratory data analysis; feature engineering; predictive modeling for regression and classification; clustering algorithms; neural networks and stochastic gradient descent methods; scalable models for Big Data sets; case studies; and programming predictive models in Python and R. Four lecture hours a week for one semester. Only one of following may be counted: Electrical and Computer Engineering 461P, Electrical Engineering 361M, 461P. Prerequisite: The following with a grade of at least C- in each: Mathematics 340L, and Computer Science 314 or 314H, or Electrical and Computer Engineering 360C (or Electrical Engineering 360C) and Biomedical Engineering 343 or Electrical and Computer Engineering 313 (or Electrical Engineering 313) and Biomedical Engineering 335 or Electrical and Computer Engineering 351K (or Electrical Engineering 351K) or Mathematics 362K.

Bachelor of Science in Electrical Engineering

Undergraduate

http://catalog.utexas.edu/undergraduate/engineering/degrees-and-programs/bs-electrical-engineering/

...and Computer Engineering Department (ECE) office about specific...Digital Communications Electrical Engineering 461P , Data Science Principles...