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CMPE 351 Advanced Data Analytics Units: 3.00
Design and implementation of complex analytics techniques; predictive algorithms at scale; deep learning; clustering at scale; advanced matrix decompositions, analytics in the Web, collaborative filtering; social network analysis; applications in specialized domains.
(Lec: 3, Lab: 0, Tut: 0)
(Lec: 3, Lab: 0, Tut: 0)
Requirements: Prerequisites: CMPE 251, ELEC 326 or MTHE 351
Corequisites:
Exclusions: CISC 351, CISC 372
Offering Term: W
CEAB Units:
Mathematics 10
Natural Sciences 0
Complementary Studies 0
Engineering Science 14
Engineering Design 12
Offering Faculty: Smith Engineering
Course Learning Outcomes:
- To provide an in-depth knowledge on the design of advanced data analytics techniques.
- To discuss how to design data pipelines for real-world applications and what are the key factors to consider.
- To understand implementation of data solutions involving advanced analytics techniques and diagnose problems.
- To critically analysis of existing data solutions and design new data analysis pipelines in context.