Akademik Dersler - Öğrenme Çıktıları ile Program Yeterlilik İlişkisi

Last Updated: 03/10/2025

0 : Does not support 1 : Low-level support 2 : Mid-level support 3 : Top level support

Learning Outcomes		Program Qualifications
		PY1	PY2	PY3	PY4	PY5	PY6	PY7	PY8	PY9	PY10	PY11	PY12	PY13	PY14	PY15
LO-1	Explains the fundamental concepts of deep learning, the structure of artificial neural networks, and their learning processes.	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
LO-2	Builds and implements basic deep learning models using the TensorFlow and/or PyTorch libraries.	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
LO-3	Compares different deep learning architectures such as CNN, RNN, LSTM, and Transformer, and applies them to appropriate problems.	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
LO-4	Analyzes deep learning methods in the context of big data, develops projects on real data sets, and interprets the results.	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-