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ECE 460J ECE 460J. Data Science Laboratory. 4 Hours.

Explore predictive modeling, regression and classification, data cleaning and preprocessing, feature engineering, unsupervised methods, principal component analysis, data clustering, model selection and feature selection, entropy and information theory, neural networks, deep learning, and machine learning for signals and time-series data. Three lecture hours and three laboratory hours a week for one semester. Only one of the following may be counted: Electrical and Computer Engineering 460J, Electrical Engineering 460J, 379K (Topic: Data Science Laboratory), 379K (Topic 24). Prerequisite: The following with a grade of at least C- in each: Biomedical Engineering 343 or Electrical and Computer Engineering 313 (or Electrical Engineering 313), or 313H; and Biomedical Engineering 335, Electrical and Computer Engineering 351K (or Electrical Engineering 351K), 351H, or Mathematics 362K; and Mathematics 340L. Credit with a grade of at least C- or registration for Aerospace Engineering 333T, Biomedical Engineering 333T, Chemical Engineering 333T, Civil Engineering 333T, Electrical and Computer Engineering 333T (or Electrical Engineering 333T), Engineering Studies 333T, Mechanical Engineering 333T, or Petroleum and Geosystems Engineering 333T.

Bachelor of Science in Electrical and Computer Engineering

Undergraduate

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

The curriculum in electrical engineering and computer engineering is designed to educate students in the fundamentals of engineering, which are built upon a foundation of mathematics, science, communication, and the liberal arts. Graduates should be equipped to advance their knowledge while contributing professionally to a rapidly changing technology. Areas in which electrical and computer engineers contribute significantly are: communications, signal processing, networks and systems, electronics and integrated circuits, energy systems and renewable energy, fields, waves and electromagnetic systems, nanoelectronics and nanotechnology, computer architecture and embedded systems, and software engineering and design. Typical career paths of graduates include design, development, management, consulting, teaching, and research. Many graduates seek further education in law, medicine, business, or engineering.