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Bachelor's

Bachelor of Science in Computer Engineering: Machine Learning and Data Science

University of Wisconsin-Madison College of Engineering 26 courses

About This Program

The Machine Learning and Data Science option in Computer Engineering prepares students for a career in computer engineering with an emphasis on machine learning and data science. The purpose of this option is to provide guidance and recognition for students pursuing this career path. The option uses 16-17 of the elective credits within the 120-credit Computer Engineering BS degree program to focus on the mathematics, tools, and practices associated with machine learning and data science in engineering. Students selecting this option must submit an option declaration form to the dean's office in Engineering Hall.

Degree Requirements

Listed Requirements 13 credits

Machine Learning and Data Science Required Courses

Code Course Title Credits
E C E 331 Introduction to Random Signal Analysis and Statistics 3
E C E 532 Matrix Methods in Machine Learning 3
E C E 539 Introduction to Artificial Neural Networks 3
COMP SCI 564 Database Management Systems: Design and Implementation 4
Total Machine Learning and Data Science Required Courses 13 credits

Machine Learning and Data Science Elective

Code Course Title Credits
E C E 431 Digital Signal Processing 3
E C E 524 Introduction to Optimization 3
E C E 533 Image Processing 3
E C E 561 Probability and Information Theory in Machine Learning 3
E C E 570 Ethics of Data for Engineers 3
COMP SCI 525 Linear Optimization 3
COMP SCI 540 Introduction to Artificial Intelligence 3
COMP SCI 567 Biomedical Image Analysis 3
COMP SCI 576 Introduction to Bioinformatics 3
COMP SCI 577 Introduction to Algorithms 4
I SY E 412 Fundamentals of Industrial Data Analytics 3
I SY E 521 Machine Learning in Action for Industrial Engineers 3
L I S 461 Data and Algorithms: Ethics and Policy 3
MATH 535 Mathematical Methods in Data Science 3
MATH 632 Introduction to Stochastic Processes 3
MATH 635 An Introduction to Brownian Motion and Stochastic Calculus 3
M S & E 460 Introduction to Computational Materials Science and Engineering 3
M S & E 561 Machine Learning in Materials 3
STAT 421 Applied Categorical Data Analysis 3
STAT 424 Statistical Experimental Design 3
STAT 456 Applied Multivariate Analysis 3
STAT 461 Financial Statistics 3

Click a course code or title to read the full course description.

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Program and course information is reproduced from each university's published academic catalog for informational purposes and may change. Always confirm current requirements with your university. We are an independent academic support service and are not affiliated with or endorsed by the universities listed.

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