diff --git a/etc/quiz-src/questions.txt b/etc/quiz-src/questions.txt
new file mode 100644
index 00000000..7f5483e5
--- /dev/null
+++ b/etc/quiz-src/questions.txt
@@ -0,0 +1,135 @@
+Lesson 1B Introduction to AI - Pre Quiz
+* A famous 19th century proto-computer engineer was
+- Charles Barkley
++ Charles Babbage
+- Charles Darwin
+* Weak AI is a system designed to solve many tasks
+- True
++ False
+* Chat bots are an example of truly intelligent systems
+- false, they are usually designed by a series of rules.
+- true, they are usually considered to be 'intelligent
++ false, but they are increasingly able to pass Turing tests as they become more sophisticated.
+
+Lesson 1E Introduction to AI - Post-Quiz
+* A top-down approach to AI is a model of reasoning called
+- strategic reasoning
++ symbolic reasoning
+- synergistic reasoning
+* A bottom-up approach to AI is based on neural networks
++ True
+- False
+* The AI Winter occurred in this era
+- 1950s
+- 1960s
++ 1970s
+
+Lesson 2B Knowledge Representation and Expert Systems: Pre-Quiz
+* The top-down approach to creating intelligent systems was based on:
+- knowledge seeking and reading
++ knowledge representation and reasoning
+- knowledge reasoning and seeking
+* Knowledge is the same as information
+- True
++ False
+* Knowledge is obtained by an:
++ active learning process
+- passive learning process
+- both of these
+
+Lesson 2E Knowledge Representation and Expert Systems: Post-Quiz
+* The simplest method of knowledge representation is:
++ algorithmic
+- symbolic
+- synergistic
+* Scenarios can represent complex situations that can unfold in time
++ true
+- false
+* Forward inference starts with initial data and then:
++ executes a reasoning loop
+- looks for a goal
+- starts over
+
+Lesson 3B Introduction to Neural Networks - Perceptron: Pre-Quiz
+* Early neural networks required
++ manual weight adjusting
+- terabytes of data
+- special reasoning
+* A simple neuron is also called a 'threshold logic unit'
++ true
+- false
+* A perceptron is a ___ type of model
+- multi-class classification
+- clustering
++ binary classification
+
+Lesson 3E Introduction to Neural Networks - Perceptron: Post-Quiz
+* To train a perceptron, find a weights vector that results in the smallest ___.
+- size
++ error
+- nodes
+* To minimize the function of weights, you can use gradient descent
++ true
+- false
+* During gradient descent, each step updates the ___
+- learning rate
++ weights
+- gradient
+
+Lesson 4B Neural Networks - Pre Quiz
+* The quality of prediction is measured by Loss function 
++ True
+- False
+* One layer network is capable of classifying ____
+- linearly joined classes
++ linearly separable classes
+- single layers of classes
+* The method of training multi-layered perceptron is called ____
++ back propagation
+- multiple propagation
+- front propagation
+
+Lesson 4E Neural Networks - Post Quiz
+* We use ____ for regression loss functions
+- absolute error
+- mean squared error
++ all of the above
+* All but one is a type of classification loss function
+- 0-1 loss
++ binary loss
+- logistic loss
+* Softmax can be used to convert inputs into probabilities
+- True
++ False
+* Cross-entropy loss is a function that can calculate similarity between two arbitrary probability distributions
++ True
+- False
+
+Lesson 5B Frameworks - Pre Quiz
+* Deep Neural Network training requires a lot of computations
++ True
+- False
+* Overfitting occurs because of ____
+- Not enough testing data
++ Too powerful model
+- Too much noise in output data
+* Bias errors are caused by our ____ not being able to capture the relationship between training data correctly.
+- model
++ algorithm
+- computer
+
+Lesson 5E Frameworks - Post Quiz
+* After compiling our model object, we train by calling ____ function
++ fit
+- train
+- teach
+* Binary cross-entropy is also called log loss
++ True
+- False
+* Tensorflow is to ____ while PyTorch is to ____
+- Facebook, Google
++ Google, Facebook
+- Microsoft, Google
+* Pred is the values predicted by the network
++ True
+- False
diff --git a/etc/quiz-src/qzmkjson.py b/etc/quiz-src/qzmkjson.py
new file mode 100644
index 00000000..90fe6cb4
--- /dev/null
+++ b/etc/quiz-src/qzmkjson.py
@@ -0,0 +1,64 @@
+src = 'questions.txt'
+dst_dir = '../quiz-app/src/assets/translations/zz'
+
+import json,os
+from copy import deepcopy
+
+from matplotlib.cbook import ls_mapper
+
+def mk_id(s): # convert from 4B/4E to numeric lesson id
+    lesson_no = int(s[:-1])
+    return lesson_no + (100 if s[-1]=='B' else 200)
+
+with open('template.json') as f:
+    doc = json.load(f)
+
+inp = open(src,encoding='utf-8').readlines()
+
+prev_q = None
+prev_l = None
+prev_l_id = None
+lessons = { }
+
+for l in inp:
+    l = l.strip()
+    if l=='': continue
+    if l.startswith('+') or l.startswith('-'): # answer
+        prev_q['answerOptions'].append({ "answerText" : l[2:], "isCorrect" :  l.startswith('+') })
+    elif l.startswith('*'):
+        if prev_q:
+            prev_l['quiz'].append(prev_q)
+        prev_q = { "questionText" : l[2:], "answerOptions" : [] };
+    elif l.startswith('Lesson'):
+        if prev_q:
+            prev_l['quiz'].append(prev_q)
+            prev_q = None
+        if prev_l is not None:
+            lessons[prev_l_id] = prev_l
+        prev_l_id = l[7:l.find(' ',7)]
+        prev_l = { "id" : mk_id(prev_l_id), "title" : l[l.find(' ',7)+1:], "quiz" : [] }
+    else:
+        print(f"Error: {l}")
+
+prev_l['quiz'].append(prev_q)
+lessons[prev_l_id] = prev_l
+
+lesson_content = {}
+for k,v in lessons.items():
+    no = int(k[:-1])
+    if no not in lesson_content.keys():
+        lesson_content[no] = deepcopy(doc)
+    lesson_content[no][0]['quizzes'].append(v)
+
+print(lesson_content[1])
+
+with open(os.path.join(dst_dir,'index.js'),'w',encoding='utf-8') as f:
+    for i,k in enumerate(lesson_content.keys()):
+        f.write(f'import x{k} from "./lesson-{k}.json";\n')
+    t = ', '.join([ f"{i} : x{k}[0]" for i,k in enumerate(lesson_content.keys())]);
+    f.write(f"const quiz = {{ {t} }}; \n");
+    f.write("export default quiz;")
+    
+for k,v in lesson_content.items():
+    with open(os.path.join(dst_dir,f"lesson-{k}.json"),'w', encoding='utf-8') as f:
+        json.dump(v,f,indent=2)
diff --git a/etc/quiz-src/template.json b/etc/quiz-src/template.json
new file mode 100644
index 00000000..a6db6bbc
--- /dev/null
+++ b/etc/quiz-src/template.json
@@ -0,0 +1,9 @@
+[
+  {
+    "title": "AI for Beginners: Quizzes",
+    "complete": "Congratulations, you completed the quiz!",
+    "error": "Sorry, try again",
+    "quizzes": [
+    ]
+  }
+]