Data Mining & Machine Learning Certificate (CSE)

The Certificate in Data Mining and Machine Learning can be awarded in conjunction with any engineering master's degree. To qualify for this certificate, students enrolled in any master's program within the McKelvey School of Engineering will need to meet the requirements listed below in addition to the standard requirements for their master's degree.

Required Courses

CSE 4107 Introduction to Machine Learning or ESE 4170 Introduction to Machine Learning and Pattern Classification3
CSE 5107 Machine Learning3
CSE 5401Advanced Algorithms3
Total Units9

Foundations Courses

Choose two courses:

CSE 4102 Introduction to Artificial Intelligence3
CSE 5103Theory of Artificial Intelligence and Machine Learning3
CSE 5104Data Mining3
CSE 5105Bayesian Methods in Machine Learning3
CSE 5109Advanced Machine Learning3
CSE 5403Algorithms for Nonlinear Optimization3
ESE 4150 Optimization3
SDS 4010 Probability or ESE 5200 Probability and Stochastic Processes3
SDS 4020 Mathematical Statistics3
CSE 5610Large Language Models3

Domain Courses

Choose one course:

CSE 4207Cloud Computing With Big Data Applications3
CSE 5108Human-In-The-Loop Computation3
CSE 5270Natural Language Processing3
ESE 5130 Large-Scale Optimization for Data Science3
CSE 5507Advanced Visualization3
CSE 5509Computer Vision3
CSE 5804Algorithms for Biosequence Comparison3
CSE 5807Algorithms for Computational Biology3
CSE 5310 AI for Health3
CSE 5370Trustworthy Autonomy3
CSE 5505Adversarial AI3

Additional Information

  • All courses must be taken for a grade.
  • Courses must be graded at a D- or better in order to count toward the certificate.
  • Students with previous courses in machine learning may place out of CSE 4107. These students will be required to complete an additional foundations course for a total of three foundations courses.

Contact Info