Eskisehir Technical University Info Package Eskisehir Technical University Info Package
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About the Program Educational Objectives Key Learning Outcomes Course Structure Diagram with Credits Field Qualifications Matrix of Course& Program Qualifications Matrix of Program Outcomes&Field Qualifications
  • Faculty Of Computer And Information Technologies
  • Artificial Intelligence And Machine Learning Pr. (English)
  • Course Structure Diagram with Credits
  • Applied Machine Learning
  • Learning Outcomes & Program Qualifications
  • Description
  • Learning Outcomes
  • Course's Contribution to Prog.
  • Learning Outcomes & Program Qualifications
  • ECTS Credit Load
0 : Does not support   1 : Low-level support   2 : Mid-level support   3 : Top level support
Learning Outcomes123456789101112
Can create complex data preprocessing and model training workflows using sklearn.pipeline and ColumnTransformer.312303123123
Can apply techniques such as SMOTE for imbalanced datasets.232323112023
Can deploy an ML model as a web service (API) using Flask or FastAPI.302331211322
Can containerize the model\'s API by writing a Dockerfile.302311213233
Can explain the difference between Data Drift and Concept Drift.132323131233
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  • PhD / Proficiency in Art
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