diff --git a/etc/quiz-app/src/assets/translations/en/index.js b/etc/quiz-app/src/assets/translations/en/index.js
index e811d147..e40c039e 100644
--- a/etc/quiz-app/src/assets/translations/en/index.js
+++ b/etc/quiz-app/src/assets/translations/en/index.js
@@ -8,13 +8,19 @@ import x7 from "./lesson-7.json";
 import x8 from "./lesson-8.json";
 import x9 from "./lesson-9.json";
 import x10 from "./lesson-10.json";
+import x11 from "./lesson-11.json";
 import x12 from "./lesson-12.json";
 import x13 from "./lesson-13.json";
 import x14 from "./lesson-14.json";
+import x15 from "./lesson-15.json";
 import x16 from "./lesson-16.json";
 import x17 from "./lesson-17.json";
 import x18 from "./lesson-18.json";
+import x19 from "./lesson-19.json";
+import x20 from "./lesson-20.json";
 import x21 from "./lesson-21.json";
+import x22 from "./lesson-22.json";
 import x23 from "./lesson-23.json";
-const quiz = { 0 : x1[0], 1 : x2[0], 2 : x3[0], 3 : x4[0], 4 : x5[0], 5 : x6[0], 6 : x7[0], 7 : x8[0], 8 : x9[0], 9 : x10[0], 10 : x12[0], 11 : x13[0], 12 : x14[0], 13 : x16[0], 14 : x17[0], 15 : x18[0], 16 : x21[0], 17 : x23[0] }; 
+import x24 from "./lesson-24.json";
+const quiz = { 0 : x1[0], 1 : x2[0], 2 : x3[0], 3 : x4[0], 4 : x5[0], 5 : x6[0], 6 : x7[0], 7 : x8[0], 8 : x9[0], 9 : x10[0], 10 : x11[0], 11 : x12[0], 12 : x13[0], 13 : x14[0], 14 : x15[0], 15 : x16[0], 16 : x17[0], 17 : x18[0], 18 : x19[0], 19 : x20[0], 20 : x21[0], 21 : x22[0], 22 : x23[0], 23 : x24[0] }; 
 export default quiz;
\ No newline at end of file
diff --git a/etc/quiz-app/src/assets/translations/en/lesson-11.json b/etc/quiz-app/src/assets/translations/en/lesson-11.json
new file mode 100644
index 00000000..0fa0f825
--- /dev/null
+++ b/etc/quiz-app/src/assets/translations/en/lesson-11.json
@@ -0,0 +1,119 @@
+[
+  {
+    "title": "AI for Beginners: Quizzes",
+    "complete": "Congratulations, you completed the quiz!",
+    "error": "Sorry, try again",
+    "quizzes": [
+      {
+        "id": 111,
+        "title": "Object Detection: Pre Quiz",
+        "quiz": [
+          {
+            "questionText": "Neural networks can only be used to classify images",
+            "answerOptions": [
+              {
+                "answerText": "true",
+                "isCorrect": false
+              },
+              {
+                "answerText": "false",
+                "isCorrect": true
+              }
+            ]
+          },
+          {
+            "questionText": "With object detection, we don't just get class of an object, but also it's ____",
+            "answerOptions": [
+              {
+                "answerText": "shape",
+                "isCorrect": false
+              },
+              {
+                "answerText": "location",
+                "isCorrect": true
+              },
+              {
+                "answerText": "type",
+                "isCorrect": false
+              }
+            ]
+          },
+          {
+            "questionText": "How many objects an object detection model can detect?",
+            "answerOptions": [
+              {
+                "answerText": "one",
+                "isCorrect": false
+              },
+              {
+                "answerText": "two",
+                "isCorrect": false
+              },
+              {
+                "answerText": "any number",
+                "isCorrect": true
+              }
+            ]
+          }
+        ]
+      },
+      {
+        "id": 211,
+        "title": "Object Detection: Post Quiz",
+        "quiz": [
+          {
+            "questionText": "Object detection model give us",
+            "answerOptions": [
+              {
+                "answerText": "object class",
+                "isCorrect": false
+              },
+              {
+                "answerText": "bounding box",
+                "isCorrect": false
+              },
+              {
+                "answerText": "both class and bounding box",
+                "isCorrect": true
+              }
+            ]
+          },
+          {
+            "questionText": "Which object detection models are faster?",
+            "answerOptions": [
+              {
+                "answerText": "one-pass models",
+                "isCorrect": true
+              },
+              {
+                "answerText": "region proposal networks",
+                "isCorrect": false
+              },
+              {
+                "answerText": "Fast R-CNN",
+                "isCorrect": false
+              }
+            ]
+          },
+          {
+            "questionText": "Which metric can be used to determine how well bounding boxes are aligned?",
+            "answerOptions": [
+              {
+                "answerText": "accuracy",
+                "isCorrect": false
+              },
+              {
+                "answerText": "precision",
+                "isCorrect": false
+              },
+              {
+                "answerText": "IoU",
+                "isCorrect": true
+              }
+            ]
+          }
+        ]
+      }
+    ]
+  }
+]
\ No newline at end of file
diff --git a/etc/quiz-app/src/assets/translations/en/lesson-12.json b/etc/quiz-app/src/assets/translations/en/lesson-12.json
index ad3b0409..9da06716 100644
--- a/etc/quiz-app/src/assets/translations/en/lesson-12.json
+++ b/etc/quiz-app/src/assets/translations/en/lesson-12.json
@@ -50,7 +50,7 @@
                 "isCorrect": false
               },
               {
-                "answerText": "encoder, Decoder",
+                "answerText": "encoder, decoder",
                 "isCorrect": true
               },
               {
diff --git a/etc/quiz-app/src/assets/translations/en/lesson-15.json b/etc/quiz-app/src/assets/translations/en/lesson-15.json
new file mode 100644
index 00000000..2d0201e2
--- /dev/null
+++ b/etc/quiz-app/src/assets/translations/en/lesson-15.json
@@ -0,0 +1,123 @@
+[
+  {
+    "title": "AI for Beginners: Quizzes",
+    "complete": "Congratulations, you completed the quiz!",
+    "error": "Sorry, try again",
+    "quizzes": [
+      {
+        "id": 115,
+        "title": "Language Modeling: Pre Quiz",
+        "quiz": [
+          {
+            "questionText": "Which of the following can be considered a language model?",
+            "answerOptions": [
+              {
+                "answerText": "Word2Vec embeddings",
+                "isCorrect": true
+              },
+              {
+                "answerText": "Embedding layer in RNN",
+                "isCorrect": false
+              },
+              {
+                "answerText": "RNN used for text classification",
+                "isCorrect": false
+              }
+            ]
+          },
+          {
+            "questionText": "A language model should be able to ____ the next word in the sentence",
+            "answerOptions": [
+              {
+                "answerText": "use",
+                "isCorrect": false
+              },
+              {
+                "answerText": "predict",
+                "isCorrect": true
+              },
+              {
+                "answerText": "guess",
+                "isCorrect": false
+              }
+            ]
+          },
+          {
+            "questionText": "Language models are trained on",
+            "answerOptions": [
+              {
+                "answerText": "language vocabulary",
+                "isCorrect": false
+              },
+              {
+                "answerText": "specially labeled data",
+                "isCorrect": false
+              },
+              {
+                "answerText": "any natural text",
+                "isCorrect": true
+              }
+            ]
+          }
+        ]
+      },
+      {
+        "id": 215,
+        "title": "Language Modeling: Post Quiz",
+        "quiz": [
+          {
+            "questionText": "Which of the architectures predicts a word from neighboring words?",
+            "answerOptions": [
+              {
+                "answerText": "CBoW",
+                "isCorrect": true
+              },
+              {
+                "answerText": "Skip-gram",
+                "isCorrect": false
+              },
+              {
+                "answerText": "N-Gram",
+                "isCorrect": false
+              }
+            ]
+          },
+          {
+            "questionText": "When we train CBoW model, we obtain",
+            "answerOptions": [
+              {
+                "answerText": "A model that can generate text",
+                "isCorrect": false
+              },
+              {
+                "answerText": "Word2Vec embedding vectors",
+                "isCorrect": true
+              },
+              {
+                "answerText": "Text classification model",
+                "isCorrect": false
+              }
+            ]
+          },
+          {
+            "questionText": "CBoW model is based on",
+            "answerOptions": [
+              {
+                "answerText": "Dense neural network",
+                "isCorrect": true
+              },
+              {
+                "answerText": "Convolutional neural network",
+                "isCorrect": false
+              },
+              {
+                "answerText": "Recurrent neural network",
+                "isCorrect": false
+              }
+            ]
+          }
+        ]
+      }
+    ]
+  }
+]
\ No newline at end of file
diff --git a/etc/quiz-app/src/assets/translations/en/lesson-16.json b/etc/quiz-app/src/assets/translations/en/lesson-16.json
index 6541b2f1..136ad56b 100644
--- a/etc/quiz-app/src/assets/translations/en/lesson-16.json
+++ b/etc/quiz-app/src/assets/translations/en/lesson-16.json
@@ -66,7 +66,7 @@
         "title": "RNN: Post Quiz",
         "quiz": [
           {
-            "questionText": "_____ takes some information from the input and hidden vector, and inserts it into the state",
+            "questionText": "_____ takes some information from the input and hidden vector, and inserts it into state",
             "answerOptions": [
               {
                 "answerText": "forget gate",
diff --git a/etc/quiz-app/src/assets/translations/en/lesson-17.json b/etc/quiz-app/src/assets/translations/en/lesson-17.json
index a9e43509..2e315862 100644
--- a/etc/quiz-app/src/assets/translations/en/lesson-17.json
+++ b/etc/quiz-app/src/assets/translations/en/lesson-17.json
@@ -39,7 +39,7 @@
             ]
           },
           {
-            "questionText": "RNN generates texts by generating the next output character for each input character",
+            "questionText": "RNN generates texts by generating next output token for each input token",
             "answerOptions": [
               {
                 "answerText": "true",
@@ -58,7 +58,7 @@
         "title": "Generative networks: Post Quiz",
         "quiz": [
           {
-            "questionText": "An output encoder converts hidden state into _____ output",
+            "questionText": "Output encoder converts hidden state into _____ output",
             "answerOptions": [
               {
                 "answerText": "one-hot-encoded",
diff --git a/etc/quiz-app/src/assets/translations/en/lesson-18.json b/etc/quiz-app/src/assets/translations/en/lesson-18.json
index de63a0ec..abda6620 100644
--- a/etc/quiz-app/src/assets/translations/en/lesson-18.json
+++ b/etc/quiz-app/src/assets/translations/en/lesson-18.json
@@ -9,7 +9,7 @@
         "title": "Transformers: Pre Quiz",
         "quiz": [
           {
-            "questionText": "Attention mechanism provides a means of _____ the impact of an inout vector on an output prediction of RNN",
+            "questionText": "Attention mechanism provides a means of _____ the imoact of an inout vector on an output prediction of RNN",
             "answerOptions": [
               {
                 "answerText": "weighting",
diff --git a/etc/quiz-app/src/assets/translations/en/lesson-19.json b/etc/quiz-app/src/assets/translations/en/lesson-19.json
new file mode 100644
index 00000000..e4650f04
--- /dev/null
+++ b/etc/quiz-app/src/assets/translations/en/lesson-19.json
@@ -0,0 +1,119 @@
+[
+  {
+    "title": "AI for Beginners: Quizzes",
+    "complete": "Congratulations, you completed the quiz!",
+    "error": "Sorry, try again",
+    "quizzes": [
+      {
+        "id": 119,
+        "title": "Named Entity Recognition: Pre Quiz",
+        "quiz": [
+          {
+            "questionText": "What is NER stands for?",
+            "answerOptions": [
+              {
+                "answerText": "Nearest Estimated Region",
+                "isCorrect": false
+              },
+              {
+                "answerText": "Nearest Entity Region",
+                "isCorrect": false
+              },
+              {
+                "answerText": "Named Entity Recognition",
+                "isCorrect": true
+              }
+            ]
+          },
+          {
+            "questionText": "An entity always consists of one token",
+            "answerOptions": [
+              {
+                "answerText": "true",
+                "isCorrect": false
+              },
+              {
+                "answerText": "false",
+                "isCorrect": true
+              }
+            ]
+          },
+          {
+            "questionText": "To train NER model, we need",
+            "answerOptions": [
+              {
+                "answerText": "Labeled dataset",
+                "isCorrect": true
+              },
+              {
+                "answerText": "Any natural text",
+                "isCorrect": false
+              },
+              {
+                "answerText": "Translated texts in two languages",
+                "isCorrect": false
+              }
+            ]
+          }
+        ]
+      },
+      {
+        "id": 219,
+        "title": "Named Entity Recognition: Post Quiz",
+        "quiz": [
+          {
+            "questionText": "NER model is essentially a ____ model",
+            "answerOptions": [
+              {
+                "answerText": "text classification",
+                "isCorrect": false
+              },
+              {
+                "answerText": "token classification",
+                "isCorrect": false
+              },
+              {
+                "answerText": "text regression",
+                "isCorrect": false
+              }
+            ]
+          },
+          {
+            "questionText": "Which neural network types can be used for NER?",
+            "answerOptions": [
+              {
+                "answerText": "RNNs",
+                "isCorrect": false
+              },
+              {
+                "answerText": "Transformers",
+                "isCorrect": false
+              },
+              {
+                "answerText": "Both RNNs and Transformers",
+                "isCorrect": true
+              }
+            ]
+          },
+          {
+            "questionText": "NER model is a good example of ____ network architecture",
+            "answerOptions": [
+              {
+                "answerText": "one-to-one",
+                "isCorrect": false
+              },
+              {
+                "answerText": "one-to-many",
+                "isCorrect": false
+              },
+              {
+                "answerText": "many-to-many",
+                "isCorrect": true
+              }
+            ]
+          }
+        ]
+      }
+    ]
+  }
+]
\ No newline at end of file
diff --git a/etc/quiz-app/src/assets/translations/en/lesson-20.json b/etc/quiz-app/src/assets/translations/en/lesson-20.json
new file mode 100644
index 00000000..79082c9a
--- /dev/null
+++ b/etc/quiz-app/src/assets/translations/en/lesson-20.json
@@ -0,0 +1,119 @@
+[
+  {
+    "title": "AI for Beginners: Quizzes",
+    "complete": "Congratulations, you completed the quiz!",
+    "error": "Sorry, try again",
+    "quizzes": [
+      {
+        "id": 120,
+        "title": "Language Models: Pre Quiz",
+        "quiz": [
+          {
+            "questionText": "What is GPT stands for?",
+            "answerOptions": [
+              {
+                "answerText": "Generic Pre-Trained network",
+                "isCorrect": false
+              },
+              {
+                "answerText": "Generative Pre-trained Transformers",
+                "isCorrect": true
+              },
+              {
+                "answerText": "Generic Positional Text",
+                "isCorrect": false
+              }
+            ]
+          },
+          {
+            "questionText": "What can GPT be used for?",
+            "answerOptions": [
+              {
+                "answerText": "Text generation",
+                "isCorrect": false
+              },
+              {
+                "answerText": "Text classification",
+                "isCorrect": false
+              },
+              {
+                "answerText": "Both text generation and other tasks",
+                "isCorrect": true
+              }
+            ]
+          },
+          {
+            "questionText": "GPT is based on transformer architecture",
+            "answerOptions": [
+              {
+                "answerText": "true",
+                "isCorrect": true
+              },
+              {
+                "answerText": "false",
+                "isCorrect": false
+              }
+            ]
+          }
+        ]
+      },
+      {
+        "id": 220,
+        "title": "Language Models: Post Quiz",
+        "quiz": [
+          {
+            "questionText": "What is zero-shot learning?",
+            "answerOptions": [
+              {
+                "answerText": "Getting an answer from pre-trained network",
+                "isCorrect": true
+              },
+              {
+                "answerText": "Training the network from scratch",
+                "isCorrect": false
+              },
+              {
+                "answerText": "Training the network only for one epoch",
+                "isCorrect": false
+              }
+            ]
+          },
+          {
+            "questionText": "Prompt engineering can be used with",
+            "answerOptions": [
+              {
+                "answerText": "Zero-shot learning",
+                "isCorrect": false
+              },
+              {
+                "answerText": "Few-shot learning",
+                "isCorrect": false
+              },
+              {
+                "answerText": "Both",
+                "isCorrect": false
+              }
+            ]
+          },
+          {
+            "questionText": "Which metric can be used to estimate quality of a language model?",
+            "answerOptions": [
+              {
+                "answerText": "accuracy",
+                "isCorrect": false
+              },
+              {
+                "answerText": "recall",
+                "isCorrect": false
+              },
+              {
+                "answerText": "perplexity",
+                "isCorrect": true
+              }
+            ]
+          }
+        ]
+      }
+    ]
+  }
+]
\ No newline at end of file
diff --git a/etc/quiz-app/src/assets/translations/en/lesson-22.json b/etc/quiz-app/src/assets/translations/en/lesson-22.json
new file mode 100644
index 00000000..378bd7f8
--- /dev/null
+++ b/etc/quiz-app/src/assets/translations/en/lesson-22.json
@@ -0,0 +1,123 @@
+[
+  {
+    "title": "AI for Beginners: Quizzes",
+    "complete": "Congratulations, you completed the quiz!",
+    "error": "Sorry, try again",
+    "quizzes": [
+      {
+        "id": 122,
+        "title": "Reinforcement Learning: Pre Quiz",
+        "quiz": [
+          {
+            "questionText": "To train RL model, we need",
+            "answerOptions": [
+              {
+                "answerText": "Simulation environment",
+                "isCorrect": true
+              },
+              {
+                "answerText": "Labeled dataset",
+                "isCorrect": false
+              },
+              {
+                "answerText": "Unlabeled dataset",
+                "isCorrect": false
+              }
+            ]
+          },
+          {
+            "questionText": "What is a good example of Reinforcement learning:",
+            "answerOptions": [
+              {
+                "answerText": "Zero-shot image classification",
+                "isCorrect": false
+              },
+              {
+                "answerText": "Zero-shot text classification",
+                "isCorrect": false
+              },
+              {
+                "answerText": "Learning to play chess",
+                "isCorrect": true
+              }
+            ]
+          },
+          {
+            "questionText": "When creating RL-based chess engine, we need to",
+            "answerOptions": [
+              {
+                "answerText": "use all existing chess matches as a dataset",
+                "isCorrect": false
+              },
+              {
+                "answerText": "let computer play against itself many times",
+                "isCorrect": true
+              },
+              {
+                "answerText": "program exhaustive search algorithm",
+                "isCorrect": false
+              }
+            ]
+          }
+        ]
+      },
+      {
+        "id": 222,
+        "title": "Reinforcement Learning: Post Quiz",
+        "quiz": [
+          {
+            "questionText": "How does RL training algorithm knows how well it did?",
+            "answerOptions": [
+              {
+                "answerText": "It achieves high accuracy",
+                "isCorrect": false
+              },
+              {
+                "answerText": "Using perplexity metric",
+                "isCorrect": false
+              },
+              {
+                "answerText": "Using reward function",
+                "isCorrect": true
+              }
+            ]
+          },
+          {
+            "questionText": "Which problems RL is applicable to?",
+            "answerOptions": [
+              {
+                "answerText": "With discrete environment",
+                "isCorrect": false
+              },
+              {
+                "answerText": "With continuous environment",
+                "isCorrect": false
+              },
+              {
+                "answerText": "Both",
+                "isCorrect": true
+              }
+            ]
+          },
+          {
+            "questionText": "In Actor-Critic model, critic predicts",
+            "answerOptions": [
+              {
+                "answerText": "Reward function",
+                "isCorrect": true
+              },
+              {
+                "answerText": "Best next action",
+                "isCorrect": false
+              },
+              {
+                "answerText": "Probability of next actions",
+                "isCorrect": false
+              }
+            ]
+          }
+        ]
+      }
+    ]
+  }
+]
\ No newline at end of file
diff --git a/etc/quiz-app/src/assets/translations/en/lesson-23.json b/etc/quiz-app/src/assets/translations/en/lesson-23.json
index a6732e6a..f9e04ca1 100644
--- a/etc/quiz-app/src/assets/translations/en/lesson-23.json
+++ b/etc/quiz-app/src/assets/translations/en/lesson-23.json
@@ -107,7 +107,7 @@
                 "isCorrect": false
               },
               {
-                "answerText": "both of the above",
+                "answerText": "both the above",
                 "isCorrect": true
               }
             ]
diff --git a/etc/quiz-app/src/assets/translations/en/lesson-24.json b/etc/quiz-app/src/assets/translations/en/lesson-24.json
new file mode 100644
index 00000000..851a0f8b
--- /dev/null
+++ b/etc/quiz-app/src/assets/translations/en/lesson-24.json
@@ -0,0 +1,136 @@
+[
+  {
+    "title": "AI for Beginners: Quizzes",
+    "complete": "Congratulations, you completed the quiz!",
+    "error": "Sorry, try again",
+    "quizzes": [
+      {
+        "id": 124,
+        "title": "Ethical and Responsible AI: Pre Quiz",
+        "quiz": [
+          {
+            "questionText": "Why we need to worry about Ethical AI?",
+            "answerOptions": [
+              {
+                "answerText": "AI is a very powerful tool and can cause harm",
+                "isCorrect": false
+              },
+              {
+                "answerText": "We need to make sure AI models do not discriminate people",
+                "isCorrect": false
+              },
+              {
+                "answerText": "Both",
+                "isCorrect": true
+              }
+            ]
+          },
+          {
+            "questionText": "Which is the example of interpretable AI?",
+            "answerOptions": [
+              {
+                "answerText": "Expert system",
+                "isCorrect": true
+              },
+              {
+                "answerText": "Neural network",
+                "isCorrect": false
+              },
+              {
+                "answerText": "Image classifier",
+                "isCorrect": false
+              }
+            ]
+          },
+          {
+            "questionText": "It is not ethical to use AI in medicine",
+            "answerOptions": [
+              {
+                "answerText": "true",
+                "isCorrect": false
+              },
+              {
+                "answerText": "false",
+                "isCorrect": true
+              }
+            ]
+          }
+        ]
+      },
+      {
+        "id": 224,
+        "title": "Ethical and Responsible AI: Post Quiz",
+        "quiz": [
+          {
+            "questionText": "Why an AI model can discriminate?",
+            "answerOptions": [
+              {
+                "answerText": "Because it may become unfriendly",
+                "isCorrect": false
+              },
+              {
+                "answerText": "Because datasets were not properly balanced",
+                "isCorrect": true
+              },
+              {
+                "answerText": "Because developers programmed it in such a way",
+                "isCorrect": false
+              }
+            ]
+          },
+          {
+            "questionText": "Which of the following is not a principle of Responsible AI?",
+            "answerOptions": [
+              {
+                "answerText": "Transparency",
+                "isCorrect": false
+              },
+              {
+                "answerText": "Fairness",
+                "isCorrect": false
+              },
+              {
+                "answerText": "Cleverness",
+                "isCorrect": true
+              }
+            ]
+          },
+          {
+            "questionText": "Accountability of an AI system means that",
+            "answerOptions": [
+              {
+                "answerText": "there should be a human being involved in taking decisions, who can take responsibility",
+                "isCorrect": true
+              },
+              {
+                "answerText": "AI system should be held responsible for its actions",
+                "isCorrect": false
+              },
+              {
+                "answerText": "AI system developers should be held responsible",
+                "isCorrect": false
+              }
+            ]
+          },
+          {
+            "questionText": "Model fairness is related to",
+            "answerOptions": [
+              {
+                "answerText": "Interpretability",
+                "isCorrect": false
+              },
+              {
+                "answerText": "Biases",
+                "isCorrect": true
+              },
+              {
+                "answerText": "Accountability",
+                "isCorrect": false
+              }
+            ]
+          }
+        ]
+      }
+    ]
+  }
+]
\ No newline at end of file
diff --git a/etc/quiz-src/questions-en.txt b/etc/quiz-src/questions-en.txt
index 82251629..41ff693c 100644
--- a/etc/quiz-src/questions-en.txt
+++ b/etc/quiz-src/questions-en.txt
@@ -258,6 +258,33 @@ Lesson 10E Generative Adversarial Networks: Post Quiz
 - Keeping balance between generator and discriminator
 + all of the above
 
+Lesson 11B Object Detection: Pre Quiz
+* Neural networks can only be used to classify images
+- true
++ false
+* With object detection, we don't just get class of an object, but also it's ____
+- shape
++ location
+- type
+* How many objects an object detection model can detect?
+- one
+- two
++ any number
+
+Lesson 11E Object Detection: Post Quiz
+* Object detection model give us
+- object class
+- bounding box
++ both class and bounding box
+* Which object detection models are faster?
++ one-pass models
+- region proposal networks
+- Fast R-CNN
+* Which metric can be used to determine how well bounding boxes are aligned?
+- accuracy
+- precision
++ IoU
+
 Lesson 12B Segmentation: Pre Quiz
 * There are ____ segmentation algorithms?
 - 1
@@ -269,7 +296,7 @@ Lesson 12B Segmentation: Pre Quiz
 - neural networks
 * Segmentation networks consist of ____ and ____ parts
 - classifier, divider
-+ encoder, Decoder
++ encoder, decoder
 - generator, discriminator
 
 Lesson 12E Segmentation: Post Quiz
@@ -337,6 +364,34 @@ Lesson 14E Embeddings: Post Quiz
 - symbol
 - number 
 
+Lesson 15B Language Modeling: Pre Quiz
+* Which of the following can be considered a language model?
++ Word2Vec embeddings
+- Embedding layer in RNN
+- RNN used for text classification
+* A language model should be able to ____ the next word in the sentence
+- use
++ predict
+- guess
+* Language models are trained on
+- language vocabulary
+- specially labeled data
++ any natural text
+ 
+Lesson 15E Language Modeling: Post Quiz
+* Which of the architectures predicts a word from neighboring words?
++ CBoW
+- Skip-gram
+- N-Gram
+* When we train CBoW model, we obtain
+- A model that can generate text
++ Word2Vec embedding vectors
+- Text classification model
+* CBoW model is based on
++ Dense neural network
+- Convolutional neural network
+- Recurrent neural network
+
 Lesson 16B RNN: Pre Quiz
 * RNN is short for?
 - regression neural network
@@ -352,7 +407,7 @@ Lesson 16B RNN: Pre Quiz
 - KNN
 
 Lesson 16E RNN: Post Quiz
-* _____ takes some information from the input and hidden vector, and inserts it into the state
+* _____ takes some information from the input and hidden vector, and inserts it into state
 - forget gate
 - output gate
 + input gate
@@ -372,12 +427,12 @@ Lesson 17B Generative networks: Pre Quiz
 + one-to-one
 - sequence-to-sequence
 - one-to-many
-* RNN generates texts by generating the next output character for each input character
+* RNN generates texts by generating next output token for each input token
 + true
 - false
 
 Lesson 17E Generative networks: Post Quiz
-* An output encoder converts hidden state into _____ output
+* Output encoder converts hidden state into _____ output
 + one-hot-encoded
 - sequence
 - number
@@ -391,7 +446,7 @@ Lesson 17E Generative networks: Post Quiz
 - one-to-many
 
 Lesson 18B Transformers: Pre Quiz
-* Attention mechanism provides a means of _____ the impact of an inout vector on an output prediction of RNN
+* Attention mechanism provides a means of _____ the imoact of an inout vector on an output prediction of RNN
 + weighting
 - training
 - testing
@@ -417,6 +472,60 @@ Lesson 18E Transformers: Post Quiz
 + 2
 - 3
 
+Lesson 19B Named Entity Recognition: Pre Quiz
+* What is NER stands for?
+- Nearest Estimated Region
+- Nearest Entity Region
++ Named Entity Recognition
+* An entity always consists of one token
+- true
++ false
+* To train NER model, we need
++ Labeled dataset
+- Any natural text
+- Translated texts in two languages
+
+Lesson 19E Named Entity Recognition: Post Quiz
+* NER model is essentially a ____ model
+- text classification
+- token classification
+- text regression
+* Which neural network types can be used for NER?
+- RNNs
+- Transformers
++ Both RNNs and Transformers
+* NER model is a good example of ____ network architecture
+- one-to-one
+- one-to-many
++ many-to-many
+
+Lesson 20B Language Models: Pre Quiz
+* What is GPT stands for?
+- Generic Pre-Trained network
++ Generative Pre-trained Transformers
+- Generic Positional Text
+* What can GPT be used for?
+- Text generation
+- Text classification
++ Both text generation and other tasks
+* GPT is based on transformer architecture
++ true
+- false
+
+Lesson 20E Language Models: Post Quiz
+* What is zero-shot learning?
++ Getting an answer from pre-trained network
+- Training the network from scratch
+- Training the network only for one epoch
+* Prompt engineering can be used with
+- Zero-shot learning
+- Few-shot learning
+- Both
+* Which metric can be used to estimate quality of a language model?
+- accuracy
+- recall
++ perplexity
+
 Lesson 21B Genetic Algorithms: Pre Quiz
 * Genetic Algorithms are based on which of the following?
 - mutations
@@ -443,6 +552,34 @@ Lesson 21E Genetic Algorithms: Post Quiz
 - 1
 + 2 
 
+Lesson 22B Reinforcement Learning: Pre Quiz
+* To train RL model, we need
++ Simulation environment
+- Labeled dataset
+- Unlabeled dataset
+* What is a good example of Reinforcement learning:
+- Zero-shot image classification
+- Zero-shot text classification
++ Learning to play chess
+* When creating RL-based chess engine, we need to
+- use all existing chess matches as a dataset
++ let computer play against itself many times
+- program exhaustive search algorithm
+
+Lesson 22E Reinforcement Learning: Post Quiz
+* How does RL training algorithm knows how well it did?
+- It achieves high accuracy
+- Using perplexity metric
++ Using reward function
+* Which problems RL is applicable to?
+- With discrete environment
+- With continuous environment
++ Both
+* In Actor-Critic model, critic predicts
++ Reward function
+- Best next action
+- Probability of next actions
+
 Lesson 23B Multi-Agent Modeling: Pre Quiz
 * By modeling the behavior of simple agents, we can understand more complex behaviors of a system.
 + true
@@ -468,4 +605,35 @@ Lesson 23E Multi-Agent Modeling: Post Quiz
 * Multi-agent systems are used in:
 - video production and systems modeling
 - games and automations
-+ both of the above
\ No newline at end of file
++ both the above
+
+Lesson 24B Ethical and Responsible AI: Pre Quiz
+* Why we need to worry about Ethical AI?
+- AI is a very powerful tool and can cause harm
+- We need to make sure AI models do not discriminate people
++ Both
+* Which is the example of interpretable AI?
++ Expert system
+- Neural network
+- Image classifier
+* It is not ethical to use AI in medicine
+- true
++ false
+
+Lesson 24E Ethical and Responsible AI: Post Quiz
+* Why an AI model can discriminate?
+- Because it may become unfriendly
++ Because datasets were not properly balanced
+- Because developers programmed it in such a way
+* Which of the following is not a principle of Responsible AI?
+- Transparency
+- Fairness
++ Cleverness
+* Accountability of an AI system means that
++ there should be a human being involved in taking decisions, who can take responsibility
+- AI system should be held responsible for its actions
+- AI system developers should be held responsible
+* Model fairness is related to
+- Interpretability
++ Biases
+- Accountability
\ No newline at end of file