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MA477 COURSE DETAILS


3 Version(s) of this Course

MA477 (Version: 2024 1) COURSE DETAILS


COURSE TITLE EFF YEAR EFF TERM DEPARTMENT CREDIT HOURS
MA477 THEORY & APPL OF DATA SCIENCE 2024 1 Mathematical Sciences 3.0 (BS=0.0, ET=0.0, MA=3.0)
SCOPE
This course builds on the foundations presented in the core probability and statistics course and the applied statistics course to develop a broad base of Advanced Data Science to some of the most common techniques in the field. The mathematical basis for each method is presented with focus on both the statistical theory and application. Topics covered may include classification and regression trees, regularization methods, splines and localized regression, and model validation.
LESSONS: 30 @ 75 min (2.000 Att/wk) LABS: 0 @ 0 min
SPECIAL REQUIREMENTS:
None

MA477 COURSE REQUISITES


TYPE COURSE EFF YEAR EFF TERM TRACK RED BOOK FLG
PRE REQUISITE  
  MA371 2013 1 1 Y
  MA376 2020 1 1 Y
  CY300 2019 2 2 Y
  MA376 2020 1 2 Y
  MA376 2020 1 3 Y
  MA486 2019 1 3 Y

MA477 (Version 2024-1) COURSE OFFERINGS


AYT #SECT/SIZE CPBLTY ENRLD WAIT SEATS CLOSED DETAILS
2024 - 8 1 18 18 0 0 18 N Hours

2024 - 9 1 18 18 0 0 18 N Hours

2025 - 2 4 18 72 58 0 14 N Hours

2025 - 8 1 18 18 0 0 18 N Hours

2025 - 9 1 18 18 0 0 18 N Hours

2026 - 2 4 19 76 52 0 24 N Hours

2027 - 2 1 18 18 3 0 15 N Hours

2028 - 2 1 18 18 0 0 18 N Hours


MA477 (Version: 2022 2) COURSE DETAILS (ARCHIVED)


COURSE TITLE EFF YEAR EFF TERM DEPARTMENT CREDIT HOURS
MA477 THEORY & APPL OF DATA SCIENCE 2022 2 Mathematical Sciences 3.0 (BS=0.0, ET=0.0, MA=3.0)
SCOPE
This course builds on the foundations presented in the core probability and statistics course and the applied statistics course to develop a broad base of Advanced Data Science to some of the most common techniques in the field. The mathematical basis for each method is presented with focus on both the statistical theory and application. Topics covered may include classification and regression trees, regularization methods, splines and localized regression, and model validation.
LESSONS: 30 @ 75 min (2.000 Att/wk) LABS: 0 @ 0 min
SPECIAL REQUIREMENTS:
None

MA477 COURSE REQUISITES


TYPE COURSE EFF YEAR EFF TERM TRACK RED BOOK FLG
PRE REQUISITE  
  MA371 2013 1 1 Y
  MA376 2020 1 1 Y
  MA486 2019 1 1 Y
  CY300 2019 2 2 Y
  MA371 2013 1 2 Y
  MA376 2020 1 2 Y

MA477 (Version: 2020 2) COURSE DETAILS (ARCHIVED)


COURSE TITLE EFF YEAR EFF TERM DEPARTMENT CREDIT HOURS
MA477 THEORY & APPL OF DATA SCIENCE 2020 2 Mathematical Sciences 3.0 (BS=0.0, ET=0.0, MA=3.0)
SCOPE
This course builds on the foundations presented in the core probability and statistics course and the applied statistics course to develop a broad base of Advanced Data Science to some of the most common techniques in the field. The mathematical basis for each method is presented with focus on both the statistical theory and application. Topics covered may include classification and regression trees, regularization methods, splines and localized regression, and model validation.
LESSONS: 30 @ 75 min (2.000 Att/wk) LABS: 0 @ 0 min
SPECIAL REQUIREMENTS:
None

MA477 COURSE REQUISITES


TYPE COURSE EFF YEAR EFF TERM TRACK RED BOOK FLG
PRE REQUISITE  
  MA376 2020 1 1 Y