Akademik Dersler - İçerik

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

Learning Outcomes	1	2	3	4	5	6	7	8	9	10	11	12
Can formulate a problem as an AI search problem (state, action, goal test).	2	2	3	1	0	1	0	3	3	1	1	2
Can implement BFS, DFS, and A* algorithms using Python and analyze the differences between them.	3	2	3	1	0	1	0	3	2	1	1	2
Can solve simple CSP problems (e.g., map coloring) using backtracking.	3	2	3	1	0	1	0	3	1	1	1	2
Apply Minimax and Alpha-Beta pruning algorithms to game trees.	3	2	3	1	0	1	1	3	1	1	1	2
Use propositional logic learned in Discrete Mathematics for knowledge representation.	2	3	2	1	0	1	0	2	1	1	1	2
Can apply Bayes’ Theorem, learned in statistics, for reasoning under uncertainty (Bayesian Networks).	2	3	2	2	1	3	1	1	2	1	2	2
Can implement simple Linear Regression and Logistic Regression models using NumPy and explain the differences between them.	3	3	2	3	1	3	3	3	1	1	1	2