Fix a couple of links

algorithms/qml/hybrid_qnn/hybrid_qnn_for_subset_majority.ipynb

@@ -64,7 +64,7 @@
     "\n",
     "The integration of quantum layers in classical neural networks may offer reduction in resources for a given functionality, as the network (or part of it) is expressed via the Hilbert space, providing different expressibility compared to classical networks.\n",
     "\n",
-    "This notebook demonstrates QNN by treating a specific function—the subset majority—for which we construct, train, and verify a hybrid classical-quantum neural network. The notebook assumes familiarity with Classiq and NN with PyTorch. See the [QML guide with Classiq](https://github.com/Classiq/classiq-library/blob/main/tutorials/documentation_materials/user_guide/qml_with_classiq_guide/qml_with_classiq_guide.ipynb)."
+    "This notebook demonstrates QNN by treating a specific function—the subset majority—for which we construct, train, and verify a hybrid classical-quantum neural network. The notebook assumes familiarity with Classiq and NN with PyTorch. See the [QML guide with Classiq](https://github.com/Classiq/classiq-library/blob/main/tutorials/popular_usage_examples/qml_with_classiq_guide/qml_with_classiq_guide.ipynb)."
    ]
   },
   {

tests/utils_for_tests.py

@@ -9,7 +9,10 @@ def iterate_notebooks() -> list[str]:
     if os.environ.get("SHOULD_TEST_ALL_FILES", "") == "true":
         notebooks_to_test = _get_all_notebooks()
     else:
-        notebooks_to_test = os.environ.get("LIST_OF_IPYNB_CHANGED", "").split()
+        notebooks_to_test = [
+            os.path.relpath(os.path.join(ROOT_DIRECTORY, path), os.getcwd())
+            for path in os.environ.get("LIST_OF_IPYNB_CHANGED", "").split()
+        ]
 
     return notebooks_to_test
 

tutorials/workshops/finance_workshops/Qmod_workshop4finance.ipynb

@@ -246,7 +246,7 @@
     "1. Make sure you define a `main` function that calls functions you create.\n",
     "2. Use `create_model` by running `qmod = create_model(main)` to construct a representation of your model.\n",
     "3. You can synthesize the model (using `qprog = synthesize(qmod)`) to obtain an implementation - a quantum program.\n",
-    "4. You can then visualize the quantum program (`show(qprog)`) or execute it using `execute(qprog)`. See: [Execution - Classiq](https://github.com/Classiq/classiq-library/blob/main/tutorials/documentation_materials/classiq_101/classiq_concepts/execute/execute.ipynb). You can also execute it with the IDE after visualizing the circuit."
+    "4. You can then visualize the quantum program (`show(qprog)`) or execute it using `execute(qprog)`. See: [Execution - Classiq](https://github.com/Classiq/classiq-library/blob/main/tutorials/classiq_101/classiq_concepts/execute/execute.ipynb). You can also execute it with the IDE after visualizing the circuit."
    ]
   },
   {
@@ -626,7 +626,7 @@
     "The `repeat` operator invokes a statement block multiple times. The statement block is specified using a Python callable, typically a `lambda` expression. Inside the block, you can refer to variables declared in the outer function scope.\n",
     "This concept is called `quantum variable capture`, equivalent to [capture](https://en.wikipedia.org/wiki/Closure_(computer_programming)) in classical languages.\n",
     "\n",
-    "See also capturing context [variables](https://github.com/Classiq/classiq-library/blob/main/tutorials/documentation_materials/classiq_101/classiq_concepts/design/quantum_variables_and_functions/quantum_variables_and_functions.ipynb) and parameters and [operators](https://docs.classiq.io/latest/qmod-reference/language-reference/operators)."
+    "See also capturing context [variables](https://github.com/Classiq/classiq-library/blob/main/tutorials/classiq_101/classiq_concepts/design/quantum_variables_and_functions/quantum_variables_and_functions.ipynb) and parameters and [operators](https://docs.classiq.io/latest/qmod-reference/language-reference/operators)."
    ]
   },
   {