feat(curriculum): add python multiple choice questions (#38890)

curriculum/challenges/_meta/python-for-penetration-testing/meta.json

@@ -26,7 +26,7 @@
     ],
     [
       "5ea9997bbec2e9bc47e94db2",
-      "Developing and Nmap Scanner part 2"
+      "Developing an Nmap Scanner part 2"
     ],
     [
       "5ea9997bbec2e9bc47e94db3",

curriculum/challenges/english/07-scientific-computing-with-python/python-for-everybody/build-your-own-functions.english.md

@@ -18,7 +18,7 @@ More resources:
 
 ```yml
 question:
-  text: 'What will the following Python program print out?
+  text: 'What will the following Python program print out?:
 <pre>def fred():<br>   print("Zap")<br><br>def jane():<br>   print("ABC")<br>
 <br>
 jane()<br>

curriculum/challenges/english/07-scientific-computing-with-python/python-for-everybody/comparing-and-sorting-tuples.english.md

@@ -18,7 +18,7 @@ More resources:
 
 ```yml
 question:
-  text: 'Which does the same thing as the following code:
+  text: 'Which does the same thing as the following code?:
 <pre>lst = []<br>for key, val in counts.items():<br>    newtup = (val, key)<br>    lst.append(newtup)<br><br>lst = sorted(lst, reverse=True)<br>print(lst)<pre>'
   answers:
     - 'print( sorted( [ (k,v) for k,v in counts.items() ] ) )'

curriculum/challenges/english/07-scientific-computing-with-python/python-for-everybody/dictionaries-and-loops.english.md

@@ -18,7 +18,7 @@ More resources:
 
 ```yml
 question:
-  text: "What will the following code print?
+  text: "What will the following code print?:
 <pre>counts = { 'chuck' : 1 , 'annie' : 42, 'jan': 100}<br>
 for key in counts:<br>    if counts[key] > 10 :<br>        print(key, counts[key])</pre>"
   answers:

curriculum/challenges/english/07-scientific-computing-with-python/python-for-everybody/files-as-a-sequence.english.md

@@ -18,12 +18,12 @@ More resources:
 
 ```yml
 question:
-  text: "What does the word 'continue' do in the middle of a loop."
+  text: "What does the word 'continue' do in the middle of a loop?"
   answers:
-    - 'skips to the code directly after the loop'
+    - 'Skips to the code directly after the loop.'
-    - 'skips to the next line in the code'
+    - 'Skips to the next line in the code.'
-    - 'skips to the next iteration of the loop'
+    - 'Skips to the next iteration of the loop.'
-    - 'skips the next block of code'
+    - 'Skips the next block of code.'
   solution: 3
 ```
 

curriculum/challenges/english/07-scientific-computing-with-python/python-for-everybody/iterations-definite-loops.english.md

@@ -17,7 +17,7 @@ videoId: hiRTRAqNlpE
 
 ```yml
 question:
-  text: 'How many lines will the following code print?
+  text: 'How many lines will the following code print?:
 <pre>for i in [2,1,5]:<br>    print(i)</pre>'
   answers:
     - '1'

curriculum/challenges/english/07-scientific-computing-with-python/python-for-everybody/iterations-loop-idioms.english.md

@@ -17,12 +17,12 @@ videoId: AelGAcoMXbI
 
 ```yml
 question:
-  text: 'Below is code to find the smallest value from a list of values. One line has an error that will cause the code to not work as expected. Which line is it?
+  text: 'Below is code to find the smallest value from a list of values. One line has an error that will cause the code to not work as expected. Which line is it?:
 <pre>
 1|smallest = None<br>
 2|print("Before:", smallest)<br>
 3|for itervar in [3, 41, 12, 9, 74, 15]:<br>
-4|    if smallest is None or itervar ⋖ smallest:<br>
+4|    if smallest is None or itervar < smallest:<br>
 5|        smallest = itervar<br>
 6|        break<br>
 7|    print("Loop:", itervar, smallest)<br>

curriculum/challenges/english/07-scientific-computing-with-python/python-for-everybody/loops-and-iterations.english.md

@@ -17,7 +17,7 @@ videoId: dLA-szNRnUY
 
 ```yml
 question:
-  text: 'What will the following code print out:
+  text: 'What will the following code print out?:
 <pre>
 n = 0<br>
 while True:<br>    if n == 3:<br>        break<br>    print(n)<br>    n = n + 1</pre>'

curriculum/challenges/english/07-scientific-computing-with-python/python-for-everybody/networking-using-urllib-in-python.md

@@ -17,15 +17,15 @@ videoId: 7lFM1T_CxBs
 
 ```yml
 question:
-  text: "What will the output of the following code be like:
+  text: "What will the output of the following code be like?:
 <pre>import urllib.request<br>
 <br>
 fhand = urllib.request.urlopen('http://data.pr4e.org/romeo.txt')<br>
 for line in fhand:<br>    print(line.decode().strip())</pre>"
   answers:
     - 'Just contents of "romeo.txt".'
-    - 'A header and the contents of "romeo.txt"'
+    - 'A header and the contents of "romeo.txt".'
-    - 'A header, a footer, and the contents of "romeo.txt"'
+    - 'A header, a footer, and the contents of "romeo.txt".'
   solution: 1
 ```
 

curriculum/challenges/english/07-scientific-computing-with-python/python-for-everybody/networking-web-scraping-with-python.english.md

@@ -20,7 +20,7 @@ More resources:
 
 ```yml
 question:
-  text: 'What Python library is used for parsing HTML documents and extracting data from HTML documents.'
+  text: 'What Python library is used for parsing HTML documents and extracting data from HTML documents?'
   answers:
     - 'socket'
     - 'http'

curriculum/challenges/english/07-scientific-computing-with-python/python-for-everybody/networking-write-a-web-browser.english.md

@@ -17,20 +17,30 @@ videoId: zjyT9DaAjx4
 
 ```yml
 question:
-  text: "What does the following code create?
+  text: |
-  <pre>
+    What does the following code create?:
-import socket<br>
+
-<br>
+    ```py
-mysock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)<br>
+    import socket
-mysock.connect(('data.pr4e.org', 80))<br>
+ 
-cmd = 'GET http://data.pr4e.org/romeo.txt HTTP/1.0\r\n\r\n'.encode()<br>
+    mysock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
-mysock.send(cmd)<br>
+    mysock.connect(('data.pr4e.org', 80))
-<br>while True:<br>    data = mysock.recv(512)<br>    if len(data) < 1:<br>        break<br>    print(data.decode(),end='')<br><br>mysock.close()</pre>"
+    cmd = 'GET http://data.pr4e.org/romeo.txt HTTP/1.0\r\n\r\n'.encode()
+    mysock.send(cmd)
+    
+    while True:
+        data = mysock.recv(512)
+            if len(data) < 1:
+                break
+            print(data.decode(),end='')
+    mysock.close()
+    ```
+
   answers:
-    - 'simple web server'
+    - 'A simple web server.'
-    - 'simple email client'
+    - 'A simple email client.'
-    - 'simple todo list'
+    - 'A simple todo list.'
-    - 'simple web browser'
+    - 'A simple web browser.'
   solution: 4
 ```
 

curriculum/challenges/english/07-scientific-computing-with-python/python-for-everybody/object-lifecycle.english.md

@@ -17,7 +17,7 @@ videoId: p1r3h_AMMIM
 
 ```yml
 question:
-  text: "What will the following program print:
+  text: "What will the following program print?:
 <pre>
 class PartyAnimal:<br>   x = 0<br>   name = ''<br>   def __init__(self, nam):<br>     self.name = nam<br>     print(self.name,'constructed')<br><br>   def party(self):<br>     self.x = self.x + 1<br>     print(self.name,'party count',self.x)<br>
 <br>

curriculum/challenges/english/07-scientific-computing-with-python/python-for-everybody/objects-a-sample-class.english.md

@@ -17,7 +17,7 @@ videoId: FiABKEuaSJ8
 
 ```yml
 question:
-  text: 'What will the following program print:
+  text: 'What will the following program print?:
 <pre>class PartyAnimal:<br>   x = 0<br><br>   def party(self) :<br>     self.x = self.x + 2<br>     print(self.x)<br>
 <br>
 an = PartyAnimal()<br>

curriculum/challenges/english/07-scientific-computing-with-python/python-for-everybody/python-dictionaries.english.md

@@ -17,7 +17,7 @@ videoId: dnzvfimrRMg
 
 ```yml
 question:
-  text: 'What does dict equal after running this code?
+  text: 'What does dict equal after running this code?:
 <pre>dict = {"Fri": 20, "Thu": 6, "Sat": 1}<br>
 dict["Thu"] = 13<br>
 dict["Sat"] = 2<br>

curriculum/challenges/english/07-scientific-computing-with-python/python-for-everybody/python-functions.english.md

@@ -19,11 +19,11 @@ videoId: 3JGF-n3tDPU
 question:
   text: 'What is the purpose of the "def" keyword in Python?'
   answers:
-    - 'It is slang that means "the following code is really cool"'
+    - 'It is slang that means "The following code is really cool."'
-    - 'It indicates the start of a function'
+    - 'It indicates the start of a function.'
-    - 'It indicates that the following indented section of code is to be stored for later'
+    - 'It indicates that the following indented section of code is to be stored for later.'
-    - 'b and c are both true'
+    - 'b and c are both true.'
-    - 'None of the above'
+    - 'None of the above.'
   solution: 4
 ```
 

curriculum/challenges/english/07-scientific-computing-with-python/python-for-everybody/python-objects.english.md

@@ -19,10 +19,10 @@ videoId: uJxGeTYy0us
 question:
   text: 'Which is NOT true about objects in Python?'
   answers:
-  - 'Objects get created and used'
+  - 'Objects get created and used.'
-  - 'Objects are bits of code and data'
+  - 'Objects are bits of code and data.'
-  - 'Objects hide detail'
+  - 'Objects hide detail.'
-  - 'Objects are one of the five standard data types'
+  - 'Objects are one of the five standard data types.'
   solution: 4
 ```
 

curriculum/challenges/english/07-scientific-computing-with-python/python-for-everybody/regular-expressions-matching-and-extracting-data.english.md

@@ -17,7 +17,7 @@ videoId: LaCZnTbQGkE
 
 ```yml
 question:
-  text: "What will the following program print:
+  text: "What will the following program print?:
 <pre>
 import re<br>
 s = 'A message from csev@umich.edu to cwen@iupui.edu about meeting @2PM'<br>

curriculum/challenges/english/07-scientific-computing-with-python/python-for-everybody/relational-database-design.english.md

@@ -17,7 +17,7 @@ videoId: AqdfbrpkbHk
 
 ```yml
 question:
-  text: 'What is the best practice for how many times a peice of string data should be stored in a database?'
+  text: 'What is the best practice for how many times a piece of string data should be stored in a database?'
   answers:
     - '0'
     - '1'

curriculum/challenges/english/07-scientific-computing-with-python/python-for-everybody/relational-databases-and-sqlite.english.md

@@ -17,7 +17,7 @@ videoId: QlNod5-kFpA
 
 ```yml
 question:
-  text: 'Which is NOT a primary data structures in a database?'
+  text: 'Which is NOT a primary data structure in a database?'
   answers:
     - 'index'
     - 'table'

curriculum/challenges/english/07-scientific-computing-with-python/python-for-everybody/strings-in-python.english.md

@@ -17,7 +17,7 @@ videoId: LYZj207fKpQ
 
 ```yml
 question:
-  text: 'What will the following code print?
+  text: 'What will the following code print?:
 <pre>for n in "banana":<br>    print(n)</pre>'
   answers:
     - 'n<br>n'

curriculum/challenges/english/07-scientific-computing-with-python/python-for-everybody/the-tuples-collection.english.md

@@ -17,7 +17,7 @@ videoId: 3Lxpladfh2k
 
 ```yml
 question:
-  text: "What will the following code print?
+  text: "What will the following code print?:
 <pre>d = dict()<br>d['quincy'] = 1<br>d['beau'] = 5<br>d['kris'] = 9<br>for (k,i) in d.items():<br>    print(k, i)</pre>"
   answers:
     - 'k i<br>k i<br>k i'

curriculum/challenges/english/07-scientific-computing-with-python/python-for-everybody/web-services-apis.english.md

@@ -20,7 +20,7 @@ question:
   text: 'What does API stand for?'
   answers:
     - 'Application Portable Intelligence'
-    - 'Accociate Programming International'
+    - 'Associate Programming International'
     - 'Application Program Interface'
     - 'Action Portable Interface'
   solution: 3

curriculum/challenges/english/07-scientific-computing-with-python/python-for-everybody/web-services-json.english.md

@@ -17,7 +17,7 @@ videoId: ZJE-U56BppM
 
 ```yml
 question:
-  text: "What will the following code print?
+  text: "What will the following code print?:
 <pre>import json<br>
 <br>
 data = '''<br>[<br>  { 'id' : '001',<br>    'x' : '2',<br>    'name' : 'Quincy'<br>  } ,<br>  { 'id' : '009',<br>    'x' : '7',<br>    'name' : 'Mrugesh'<br>  }<br>]'''<br>

curriculum/challenges/english/07-scientific-computing-with-python/python-for-everybody/web-services-service-oriented-approach.english.md

@@ -17,7 +17,7 @@ videoId: muerlsCHExI
 
 ```yml
 question:
-  text: 'With a services oriented approach to developing web apps, where is the data located.'
+  text: 'With a services oriented approach to developing web apps, where is the data located?'
   answers:
     - 'Spread across many computer systems connected via the internet or internal network.'
     - 'Within different services on the main web server.'

curriculum/challenges/english/07-scientific-computing-with-python/python-for-everybody/web-services-xml.english.md

@@ -17,7 +17,7 @@ videoId: _pZ0srbg7So
 
 ```yml
 question:
-  text: 'What is wrong with the following XML?
+  text: 'What is wrong with the following XML?:
 <pre>&ltperson&gt<br>
 &ltname>Chuck&lt/name><br>
 &ltphone type="intl"><br>  +1 734 303 4456<br>

curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/data-cleaning-and-visualizations.english.md

@@ -15,7 +15,8 @@ videoId: mHjxzFS5_Z0
 
 ```yml
 question:
-  text: 'When using Matplotlib''s global API, what does the order of numbers mean here <pre>plt.subplot(1, 2, 1)</pre>'
+  text: |
+    When using Matplotlib's global API, what does the order of numbers mean here?: `plt.subplot(1, 2, 1)`
   answers:
     - 'My figure will have one column, two rows, and I am going to start drawing in the first (left) plot.'
     - 'I am going to start drawing in the first (left) plot, my figure will have two rows, and my figure will have one column.'

curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/data-cleaning-duplicates.english.md

@@ -15,7 +15,8 @@ videoId: kj7QqjXhH6A
 
 ```yml
 question:
-  text: 'The Python method <code>.duplicated()</code> returns a boolean Series for your DataFrame. <code>True</code> is the return value for rows that:'
+  text: |
+    The Python method `.duplicated()` returns a boolean Series for your DataFrame. `True` is the return value for rows that:
   answers:
     - contain a duplicate, where the value for the row contains the first occurrence of that value.
     - contain a duplicate, where the value for the row is at least the second occurrence of that value.

curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/data-cleaning-introduction.english.md

@@ -15,12 +15,39 @@ videoId: ovYNhnltVxY
 
 ```yml
 question:
-  text: Question
+  text: |
+    What will the following code print out?:
+
+    ```py
+    import pandas as pd
+    import numpy as np
+
+    s = pd.Series(['a', 3, np.nan, 1, np.nan])
+
+    print(s.notnull().sum())
+    ```
+
   answers:
-    - one
+    - '3'
-    - two
+    - |
-    - three
+      ```
-  solution: 3
+      0     True
+      1     True
+      2    False
+      3     True
+      4    False
+      dtype: bool
+      ```
+    - |
+      ```
+      0    False
+      1    False
+      2     True
+      3    False
+      4     True
+      dtype: bool
+      ```
+  solution: 1
 ```
 
 </section>

curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/data-cleaning-with-dataframes.english.md

@@ -15,12 +15,48 @@ videoId: sTMN_pdI6S0
 
 ```yml
 question:
-  text: Question
+  text: |
+    What will the following code print out?:
+
+    ```py
+    import pandas as pd
+    import numpy as np
+
+    s = pd.Series([np.nan, 1, 2, np.nan, 3])
+    s = s.fillna(method='ffill')
+
+    print(s)
+    ```
+
   answers:
-    - one
+    - |
-    - two
+      ```
-    - three
+      0    1.0
-  solution: 3
+      1    1.0
+      2    2.0
+      3    3.0
+      4    3.0
+      dtype: float64
+      ```
+    - |
+      ```
+      0    NaN
+      1    1.0
+      2    2.0
+      3    2.0
+      4    3.0
+      dtype: float64
+      ```
+    - |
+      ```
+      0    NaN
+      1    1.0
+      2    2.0
+      3    NaN
+      4    3.0
+      dtype: float64
+      ```
+  solution: 2
 ```
 
 </section>

curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/how-to-use-jupyter-notebooks-intro.english.md

@@ -15,11 +15,11 @@ videoId: h8caJq2Bb9w
 
 ```yml
 question:
-  text: Question
+  text: What is *not* allowed in a Jupyter Notebook's cell?
   answers:
-    - one
+    - "Markdown"
-    - two
+    - "Python code"
-    - three
+    - "An Excel sheet"
   solution: 3
 ```
 

curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/introduction-to-data-analysis.english.md

@@ -15,12 +15,13 @@ videoId: VJrP2FUzKP0
 
 ```yml
 question:
-  text: Question
+  text: "Why should you choose R over Python for data analysis?"
   answers:
-    - one
+    - "It's simple to learn."
-    - two
+    - "It's better at dealing with advanced statistical methods."
-    - three
+    - "There are many powerful libraries that support R."
-  solution: 3
+    - "It's free and open source."
+  solution: 2
 ```
 
 </section>

curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/jupyter-notebooks-importing-and-exporting-data.english.md

@@ -15,12 +15,14 @@ videoId: k1msxD3JIxE
 
 ```yml
 question:
-  text: Question
+  text: "What kind of data can you import and work with in a Jupyter Notebook?"
   answers:
-    - one
+    - "Excel files."
-    - two
+    - "CSV files."
-    - three
+    - "XML files."
-  solution: 3
+    - "Data from an API."
+    - "All of the above."
+  solution: 5
 ```
 
 </section>

curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/numpy-arrays.english.md

@@ -15,11 +15,33 @@ videoId: VDYVFHBL1AM
 
 ```yml
 question:
-  text: Question
+  text: |
+    What will the following code print out?:
+
+    ```py
+    A = np.array([
+        ['a', 'b', 'c'],
+        ['d', 'e', 'f'],
+        ['g', 'h', 'i']
+    ])
+
+    print(A[:, :2])
+    ```
+
   answers:
-    - one
+    - "[['a' 'b']]"
-    - two
+    - |
-    - three
+      ```
+      [['b' 'c']
+      ['e' 'f']
+      ['h' 'i']]
+      ```
+    - |
+      ```
+      [['a' 'b']
+      ['d' 'e']
+      ['g' 'h']]
+      ```
   solution: 3
 ```
 

curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/numpy-boolean-arrays.english.md

@@ -15,12 +15,20 @@ videoId: N1ttsMmcVMM
 
 ```yml
 question:
-  text: Question
+  text: |
+    What will the following code print out?:
+
+    ```py
+    a = np.arange(5)
+
+    print(a <= 3)
+    ```
   answers:
-    - one
+    - "[False, False, False, False, True]"
-    - two
+    - "[5]"
-    - three
+    - "[0, 1, 2, 3]"
-  solution: 3
+    - "[True, True, True, True, False]"
+  solution: 4
 ```
 
 </section>

curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/numpy-introduction-a.english.md

@@ -15,12 +15,12 @@ videoId: P-JjV6GBCmk
 
 ```yml
 question:
-  text: Question
+  text: "Why is Numpy an important, but unpopular Python library?"
   answers:
-    - one
+    - "Often you won't work directly with Numpy."
-    - two
+    - "It's is extremely slow."
-    - three
+    - "Working with Numpy is difficult."
-  solution: 3
+  solution: 1
 ```
 
 </section>

curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/numpy-introduction-b.english.md

@@ -15,12 +15,14 @@ videoId: YIqgrNLAZkA
 
 ```yml
 question:
-  text: Question
+  text: |
+    About how much memory does the integer `5` consume in plain Python?
   answers:
-    - one
+    - 32 bits
-    - two
+    - 20 bytes
-    - three
+    - 16 bytes
-  solution: 3
+    - 8 bits
+  solution: 2
 ```
 
 </section>

curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/numpy-operations.english.md

@@ -15,12 +15,19 @@ videoId: eqSVcJbaPdk
 
 ```yml
 question:
-  text: Question
+  text: |
+    What is the value of `a` after you run the following code?:
+
+    ```py
+    a = np.arange(5)
+    a + 20
+    ```
+
   answers:
-    - one
+    - "[20, 21, 22, 24, 24]"
-    - two
+    - "[0, 1, 2, 3, 4, 5]"
-    - three
+    - "[25, 26, 27, 28, 29]"
-  solution: 3
+  solution: 2
 ```
 
 </section>

curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/pandas-condtitional-selection-and-modifying-dataframes.english.md

@@ -15,12 +15,51 @@ videoId: BFlH0fN5xRQ
 
 ```yml
 question:
-  text: Question
+  text: |
+    What will the following code print out?:
+
+    ```py
+    import pandas as pd
+
+    certificates_earned = pd.DataFrame({
+        'Certificates': [8, 2, 5, 6],
+        'Time (in months)': [16, 5, 9, 12]
+    })
+    names = ['Tom', 'Kris', 'Ahmad', 'Beau']
+
+    certificates_earned.index = names
+    longest_streak = pd.Series([13, 11, 9, 7], index=names)
+    certificates_earned['Longest streak'] = longest_streak
+
+    print(certificates_earned)
+    ```
+
   answers:
-    - one
+    - |
-    - two
+      ```
-    - three
+      Tom      13
-  solution: 3
+      Kris     11
+      Ahmad     9
+      Beau      7
+      Name: Longest streak, dtype: int64
+      ```
+    - |
+      ```
+            Certificates  Time (in months)  Longest streak
+      Tom               8                16              13
+      Kris              2                 5              11
+      Ahmad             5                 9               9
+      Beau              6                12               7
+      ```
+    - |
+      ```
+            Certificates   Longest streak
+      Tom               8               13
+      Kris              2               11
+      Ahmad             5                9
+      Beau              6                7
+      ```
+  solution: 2
 ```
 
 </section>

curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/pandas-creating-columns.english.md

@@ -15,11 +15,37 @@ videoId: _sSo2XZoB3E
 
 ```yml
 question:
-  text: Question
+  text: |
+    What code would add a "Certificates per month" column to the `certificates_earned` DataFrame like the one below?:
+
+    ```
+          Certificates  Time (in months)  Certificates per month
+    Tom               8                16                    0.50
+    Kris              2                 5                    0.40
+    Ahmad             5                 9                    0.56
+    Beau              6                12                    0.50
+    ```
+
   answers:
-    - one
+    - |
-    - two
+      ```py
-    - three
+      certificates_earned['Certificates'] /
+      certificates_earned['Time (in months)']
+      ```
+    - |
+      ```py
+      certificates_earned['Certificates per month'] = round(
+          certificates_earned['Certificates'] / 
+          certificates_earned['Time (in months)']
+      )
+      ```
+    - |
+      ```py
+      certificates_earned['Certificates per month'] = round(
+          certificates_earned['Certificates'] /
+          certificates_earned['Time (in months)'], 2
+      )
+      ```
   solution: 3
 ```
 

curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/pandas-dataframes.english.md

@@ -15,11 +15,43 @@ videoId: 7SgFBYXaiH0
 
 ```yml
 question:
-  text: Question
+  text: |
+    What will the following code print out?:
+
+    ```py
+    import pandas as pd
+
+    certificates_earned = pd.DataFrame({
+        'Certificates': [8, 2, 5, 6],
+        'Time (in months)': [16, 5, 9, 12]
+    })
+
+    certificates_earned.index = ['Tom', 'Kris', 'Ahmad', 'Beau']
+
+    print(certificates_earned.iloc[2])
+    ```
+
   answers:
-    - one
+    - |
-    - two
+      ```
-    - three
+      Tom      16
+      Kris      5
+      Ahmad     9
+      Beau     12
+      Name: Time (in months), dtype: int64
+      ```
+    - |
+      ```
+      Certificates         6
+      Time (in months)    12
+      Name: Beau, dtype: int64
+      ```
+    - |
+      ```
+      Certificates        5
+      Time (in months)    9
+      Name: Ahmad, dtype: int64
+      ```
   solution: 3
 ```
 

curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/pandas-indexing-and-conditional-selection.english.md

@@ -15,11 +15,42 @@ videoId: -ZOrgV_aA9A
 
 ```yml
 question:
-  text: Question
+  text: |
+    What will the following code print out?:
+
+    ```py
+    import pandas as pd
+
+    certificates_earned = pd.Series(
+        [8, 2, 5, 6], 
+        index=['Tom', 'Kris', 'Ahmad', 'Beau']
+    )
+
+    print(certificates_earned[certificates_earned > 5])
+    ```
+
   answers:
-    - one
+    - |
-    - two
+      ```
-    - three
+      Tom      True
+      Kris     False
+      Ahmad    False
+      Beau     True
+      dtype: int64
+      ```
+    - |
+      ```
+      Tom      8
+      Ahmad    5
+      Beau     6
+      dtype: int64
+      ```
+    - |
+      ```
+      Tom      8
+      Beau     6
+      dtype: int64
+      ```
   solution: 3
 ```
 

curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/pandas-introduction.english.md

@@ -15,12 +15,46 @@ videoId: 0xACW-8cZU0
 
 ```yml
 question:
-  text: Question
+  text: |
+    What will the following code print out?:
+
+    ```py
+    import pandas as pd
+
+    certificates_earned = pd.Series(
+        [8, 2, 5, 6], 
+        index=['Tom', 'Kris', 'Ahmad', 'Beau']
+    )
+
+    print(certificates_earned)
+    ```
+
   answers:
-    - one
+    - |
-    - two
+      ```
-    - three
+      Tom      8
-  solution: 3
+      Kris     2
+      Ahmad    5
+      Beau     6
+      dtype: int64
+      ```
+    - |
+      ```
+      Kris     2
+      Ahmad    5
+      Beau     6
+      Tom      8
+      dtype: int64
+      ```
+    - |
+      ```
+      Tom      8
+      Kris     2
+      Ahmad    5
+      Beau     6
+      Name: certificates_earned dtype: int64
+      ```
+  solution: 1
 ```
 
 </section>

curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/python-functions-and-collections.english.md

@@ -15,12 +15,12 @@ videoId: NzpU17ZVlUw
 
 ```yml
 question:
-  text: Question
+  text: What is the main difference between lists and tuples in Python?
   answers:
-    - one
+    - Tuples are immutable.
-    - two
+    - Lists are ordered.
-    - three
+    - Tuples are unordered.
-  solution: 3
+  solution: 1
 ```
 
 </section>

curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/reading-data-from-databases.english.md

@@ -17,9 +17,9 @@ videoId: MtgXS1MofRw
 question:
   text: What method does a <code>Cursor</code> instance have and what does it allow?
   answers:
-    - The <code>Cursor</code> instance has a <code>.Run()</code> method which allows you to run SQL queries.
+    - The <code>Cursor</code> instance has a <code>.run()</code> method which allows you to run SQL queries.
-    - The <code>Cursor</code> instance has a <code>.Select()</code> method which allows you to select records.
+    - The <code>Cursor</code> instance has a <code>.select()</code> method which allows you to select records.
-    - The <code>Cursor</code> instance has a <code>.Execute()</code> method which will receive SQL parameters to run against the database.
+    - The <code>Cursor</code> instance has an <code>.execute()</code> method which will receive SQL parameters to run against the database.
   solution: 3
 ```
 

curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/reading-data-introduction.english.md

@@ -15,12 +15,35 @@ videoId: cDnt02BcHng
 
 ```yml
 question:
-  text: Question
+  text: |
+    Given a file named `certificates.csv` with these contents:
+
+    ```
+    Name$Certificates$Time (in months)
+    Tom$8$16
+    Kris$2$5
+    Ahmad$5$9
+    Beau$6$12
+    ```
+
+    Fill in the blanks for the missing arguments below:
+
+    ```py
+    import csv
+
+    with open(___, 'r') as fp:
+        reader = csv.reader(fp, delimiter=___)
+        next(reader)
+        for index, values in enumerate(reader):
+            name, certs_num, months_num = values
+            print(f"{name} earned {___} certificates in {months_num} months")
+    ```
+  
   answers:
-    - one
+    - <code>'certificates.csv', '-', values</code>
-    - two
+    - <code>'certificates.csv', '$', certs_num</code>
-    - three
+    - <code>'certificates', '$', certs_num</code>
-  solution: 3
+  solution: 2
 ```
 
 </section>

curriculum/challenges/english/08-data-analysis-with-python/numpy/accessing-and-changing-elements,-rows,-columns.english.md

@@ -15,11 +15,25 @@ videoId: v-7Y7koJ_N0
 
 ```yml
 question:
-  text: Question
+  text: |
+    What code would change the values in the 3rd column of both of the following Numpy arrays to 20?:
+
+    ```py
+    a = np.array([[1, 2, 3, 4, 5], [6, 7, 8, 9, 10]])
+
+    # Output:
+    # [[ 1  2  3  4  5]
+    # [ 6  7 20  9 10]]
+    ```
   answers:
-    - one
+    - |
-    - two
+      `a[:, 3] = 20`
-    - three
+    - |
+      `a[2, :] = 20`
+    - |
+      `a[:, 2] = 20`
+    - |
+      `a[1, 2] = 20`
   solution: 3
 ```
 

curriculum/challenges/english/08-data-analysis-with-python/numpy/basics-of-numpy.english.md

@@ -15,7 +15,7 @@ videoId: f9QrZrKQMLI
 
 ```yml
 question:
-  text: 'What will the following code print:<pre>b = np.array([[1.0,2.0,3.0],[3.0,4.0,5.0]])<br>print(b)</pre>'
+  text: 'What will the following code print?:<pre>b = np.array([[1.0,2.0,3.0],[3.0,4.0,5.0]])<br>print(b)</pre>'
   answers:
     - '<pre>[[1.0 2.0 3.0]<br>[3.0 4.0 5.0]]<pre>'
     - '<pre>[[1. 2. 3.]<br>[3. 4. 5.]]<pre>'

curriculum/challenges/english/08-data-analysis-with-python/numpy/copying-arrays-warning.english.md

@@ -15,12 +15,25 @@ videoId: iIoQ0_L0GvA
 
 ```yml
 question:
-  text: Question
+  text: |
+    What is the value of `a` after running the following code?:
+
+    ```py
+    import numpy as np
+
+    a = np.array([1, 2, 3, 4, 5])
+    b = a
+    b[2] = 20
+    ```
+
   answers:
-    - one
+    - |
-    - two
+      `[1, 2, 3, 4, 5]`
-    - three
+    - |
-  solution: 3
+      `[1, 2, 20, 4, 5]`
+    - |
+      `[1, 20, 3, 4, 5]`
+  solution: 2
 ```
 
 </section>

curriculum/challenges/english/08-data-analysis-with-python/numpy/initialize-array-problem.english.md

@@ -15,12 +15,46 @@ videoId: 0jGfH8BPfOk
 
 ```yml
 question:
-  text: Question
+  text: |
+    What is another way to produce the following array?:
+
+    ```
+    [[1. 1. 1. 1. 1.]
+    [1. 0. 0. 0. 1.]
+    [1. 0. 9. 0. 1.]
+    [1. 0. 0. 0. 1.]
+    [1. 1. 1. 1. 1.]]
+    ```
+
   answers:
-    - one
+    - |
-    - two
+      ```py
-    - three
+      output = np.ones((5, 5))
-  solution: 3
+
+      z = np.zeros((3, 3))
+      z[1, 1] = 9
+
+      output[1:-1, 1:-1] = z
+      ```
+    - |
+      ```py
+      output = np.ones((5, 5))
+
+      z = np.zeros((3, 3))
+      z[1, 1] = 9
+
+      output[1:3, 1:3] = z
+      ```
+    - |
+      ```py
+      output = np.ones((5, 5))
+
+      z = np.zeros((3, 3))
+      z[1, 1] = 9
+
+      output[4:1, 4:1] = z
+      ```
+  solution: 1
 ```
 
 </section>

curriculum/challenges/english/08-data-analysis-with-python/numpy/initializing-different-arrays.english.md

@@ -15,12 +15,30 @@ videoId: CEykdsKT4U4
 
 ```yml
 question:
-  text: Question
+  text: |
+    What will the following code print?:
+    
+    ```py
+    a = np.array([[1, 2, 3, 4, 5], [6, 7, 8, 9, 10]])
+
+    print(np.full_like(a, 100))
+    ```
   answers:
-    - one
+    - |
-    - two
+      ```
-    - three
+      [[100 100 100 100 100]]
-  solution: 3
+      ```
+    - |
+      ```
+      [[100 100 100 100 100]
+      [100 100 100 100 100]]
+      ```
+    - |
+      ```
+      [[ 1  2  3  4  5]
+      [ 6  7 20  9 10]]
+      ```
+  solution: 2
 ```
 
 </section>

curriculum/challenges/english/08-data-analysis-with-python/numpy/loading-data-and-advanced-indexing.english.md

@@ -15,11 +15,42 @@ videoId: tUdBZ7pF8Jg
 
 ```yml
 question:
-  text: Question
+  text: |
+    Given a file named `data.txt` with these contents:
+
+    ```
+    29,97,32,100,45
+    15,88,5,75,22
+    ```
+
+    What code would produce the following array?:
+
+    ```py
+    [29. 32. 45. 15.  5. 22.]
+    ```
+  
   answers:
-    - one
+    - |
-    - two
+      ```
-    - three
+      filedata = np.genfromtxt('data.txt', delimiter=',')
+      output = np.any(filedata < 50)
+
+      print(output)
+      ```
+    - |
+      ```
+      filedata = np.genfromtxt('data.txt', delimiter=',')
+      output = np.all(filedata < 50, axis=1)
+
+      print(output)
+      ```
+    - |
+      ```
+      filedata = np.genfromtxt('data.txt', delimiter=',')
+      output = filedata[filedata < 50]
+
+      print(output)
+      ```
   solution: 3
 ```
 

curriculum/challenges/english/08-data-analysis-with-python/numpy/mathematics.english.md

@@ -15,12 +15,22 @@ videoId: 7txegvyhtVk
 
 ```yml
 question:
-  text: Question
+  text: |
+    What is the value of `b` after running the following code?:
+
+    ```py
+    import numpy as np
+
+    a = np.array(([1, 2, 3, 4, 5], [6, 7, 8, 9, 10]))
+    b = np.max(a, axis=1).sum()
+    ```
+
   answers:
-    - one
+    - '10'
-    - two
+    - '7'
-    - three
+    - '5'
-  solution: 3
+    - '15'
+  solution: 4
 ```
 
 </section>

curriculum/challenges/english/08-data-analysis-with-python/numpy/reorganizing-arrays.english.md

@@ -15,12 +15,35 @@ videoId: VNWAQbEM-C8
 
 ```yml
 question:
-  text: Question
+  text: |
+    What code would produce the following array?:
+
+    ```
+    [[1. 1.]
+    [1. 1.]
+    [1. 1.]
+    [1. 1.]]
+    ```
   answers:
-    - one
+    - |
-    - two
+      ```py
-    - three
+      a = np.ones((2, 4))
-  solution: 3
+      b = a.reshape((4, 2))
+      print(b)
+      ```
+    - |
+      ```py
+      a = np.ones((2, 4))
+      b = a.reshape((2, 4))
+      print(b)
+      ```
+    - |
+      ```py
+      a = np.ones((2, 4))
+      b = a.reshape((8, 1))
+      print(b)
+      ```
+  solution: 1
 ```
 
 </section>

curriculum/challenges/english/08-data-analysis-with-python/numpy/what-is-numpy.english.md

@@ -15,12 +15,13 @@ videoId: 5Nwfs5Ej85Q
 
 ```yml
 question:
-  text: Question
+  text: 'Why are Numpy arrays faster than regular Python lists?:'
   answers:
-    - one
+    - Numpy does not perform type checking while iterating through objects.
-    - two
+    - Numpy uses fixed types.
-    - three
+    - Numpy uses contiguous memory.
-  solution: 3
+    - All of the above.
+  solution: 4
 ```
 
 </section>

curriculum/challenges/english/09-information-security/python-for-penetration-testing/creating-a-tcp-client.english.md

@@ -15,12 +15,17 @@ videoId: ugYfJNTawks
 
 ```yml
 question:
-  text: Question
+  text: |
+    Which socket object method lets you set the maximum amount of data your client accepts at once?
+
   answers:
-    - one
+    - |
-    - two
+      `.recv(1024)`
-    - three
+    - |
-  solution: 3
+      `.decode('ascii')`
+    - |
+      `.connect(host, port)`
+  solution: 1
 ```
 
 </section>

curriculum/challenges/english/09-information-security/python-for-penetration-testing/developing-a-banner-grabber.english.md

@@ -15,11 +15,23 @@ videoId: CeGW761BIsA
 
 ```yml
 question:
-  text: Question
+  text: |
+    Fill in the blanks to complete the `banner` function below:
+
+    ```py
+    def banner(ip, port):
+        s = socket.socket()
+        s.____((ip, ____))
+        print(s.recv(1024))
+    ```
+
   answers:
-    - one
+    - |
-    - two
+      `connect`, `port`
-    - three
+    - |
+      `getsockname`, `'1-1024'`
+    - |
+      `connect`, `int(port)`
   solution: 3
 ```
 

curriculum/challenges/english/09-information-security/python-for-penetration-testing/developing-a-port-scanner.english.md

@@ -15,11 +15,15 @@ videoId: z_qkqZS7KZ4
 
 ```yml
 question:
-  text: Question
+  text: |
+    What is the main difference between the `.connect()` and `.connect_ex()` methods?
+
   answers:
-    - one
+    - There is no difference between the two methods.
-    - two
+    - |
-    - three
+      If there is an error or if no host is found, `.connect()` returns an error code while `.connect_ex()` raises an exception.
+    - |
+      If there is an error or if no host is found, `.connect()` raises an exception while `.connect_ex()` returns an error code.
   solution: 3
 ```
 

curriculum/challenges/english/09-information-security/python-for-penetration-testing/developing-an-nmap-scanner-part-1.english.md

@@ -15,11 +15,16 @@ videoId: jYk9XaGoAnk
 
 ```yml
 question:
-  text: Question
+  text: |
+    What is the correct command to install the Python 3 version of the `python-nmap` library?
+
   answers:
-    - one
+    - |
-    - two
+      `sudo apt install python-nmap`
-    - three
+    - |
+      `pip install python-nmap`
+    - |
+      `pip3 install python-nmap`
   solution: 3
 ```
 

curriculum/challenges/english/09-information-security/python-for-penetration-testing/developing-an-nmap-scanner-part-2.english.md

@@ -0,0 +1,32 @@
+---
+id: 5ea9997bbec2e9bc47e94db2
+title: Developing an Nmap Scanner part 2
+challengeType: 11
+isHidden: true
+videoId: a98PscnUsTg
+---
+
+## Description
+<section id='description'>
+</section>
+
+## Tests
+<section id='tests'>
+
+```yml
+question:
+  text: |
+    Which of the following allows you to scan for UDP ports between 21 to 443?
+
+  answers:
+    - |
+      `.scan(ip_addr, '21-443', '-v -sU')`
+    - |
+      `.scan(ip_addr, '1-1024', '-v -sS')`
+    - |
+      `.scan(ip_addr, '21-443', '-v -sS')`
+  solution: 1
+```
+
+</section>
+

curriculum/challenges/english/09-information-security/python-for-penetration-testing/developing-and-nmap-scanner-part-2.english.md

@@ -1,27 +0,0 @@
----
-id: 5ea9997bbec2e9bc47e94db2
-title: Developing and Nmap Scanner part 2
-challengeType: 11
-isHidden: true
-videoId: a98PscnUsTg
----
-
-## Description
-<section id='description'>
-</section>
-
-## Tests
-<section id='tests'>
-
-```yml
-question:
-  text: Question
-  answers:
-    - one
-    - two
-    - three
-  solution: 3
-```
-
-</section>
-

curriculum/challenges/english/09-information-security/python-for-penetration-testing/introduction-and-setup.english.md

@@ -15,12 +15,14 @@ videoId: XeQ7ZKtb998
 
 ```yml
 question:
-  text: Question
+  text: |
+    What code editor and extension does the instructor recommend for developing penetration testing tools in Python?
+
   answers:
-    - one
+    - Atom and the atom-python-run extension.
-    - two
+    - VSCode and Microsoft's Python extension.
-    - three
+    - Sublime Text and the Anaconda package.
-  solution: 3
+  solution: 2
 ```
 
 </section>

curriculum/challenges/english/09-information-security/python-for-penetration-testing/understanding-sockets-and-creating-a-tcp-server.english.md

@@ -15,11 +15,16 @@ videoId: F1QI9tNuDQg
 
 ```yml
 question:
-  text: Question
+  text: |
+    Which of the following functions creates a socket object?
+
   answers:
-    - one
+    - |
-    - two
+      `socket.bind((host, port))`
-    - three
+    - |
+      `socket.gethostbyname()`
+    - |
+      `socket.socket(socket.AF_INET, socket.SOCK_STREAM)`
   solution: 3
 ```
 

curriculum/challenges/english/11-machine-learning-with-python/how-neural-networks-work/deep-learning-demystified.english.md

@@ -15,12 +15,14 @@ videoId: bejQ-W9BGJg
 
 ```yml
 question:
-  text: Question
+  text: How should you assign weights to input neurons before training your network for the first time?
+  
   answers:
-    - one
+    - From smallest to largest.
-    - two
+    - Completely randomly.
-    - three
+    - Alphabetically.
-  solution: 3
+    - None of the above.
+  solution: 2
 ```
 
 </section>

curriculum/challenges/english/11-machine-learning-with-python/how-neural-networks-work/how-convolutional-neural-networks-work.english.md

@@ -15,12 +15,13 @@ videoId: Y5M7KH4A4n4
 
 ```yml
 question:
-  text: Question
+  text: When are Convolutional Neural Networks not useful?
+
   answers:
-    - one
+    - If your data can't be made to look like an image, or if you can rearrange elements of your data and it's still just as useful.
-    - two
+    - If your data is made up of different 2D or 3D images.
-    - three
+    - If your data is text or sound based.
-  solution: 3
+  solution: 1
 ```
 
 </section>

curriculum/challenges/english/11-machine-learning-with-python/how-neural-networks-work/how-deep-neural-networks-work.english.md

@@ -15,12 +15,13 @@ videoId: zvalnHWGtx4
 
 ```yml
 question:
-  text: Question
+  text: Why is it better to calculate the gradient (slope) directly rather than numerically?
+
   answers:
-    - one
+    - It is computationally expensive to go back through the entire neural network and adjust the weights for each layer of the neural network.
-    - two
+    - It is more accurate.
-    - three
+    - There is no difference between the two methods.
-  solution: 3
+  solution: 1
 ```
 
 </section>

curriculum/challenges/english/11-machine-learning-with-python/how-neural-networks-work/recurrent-neural-networks-rnn-and-long-short-term-memory-lstm.english.md

@@ -15,11 +15,13 @@ videoId: UVimlsy9eW0
 
 ```yml
 question:
-  text: Question
+  text: |
+    What are the main neural network components that make up a Long Short Term Memory network?
+
   answers:
-    - one
+    - New information and prediction.
-    - two
+    - Prediction, collected possibilities, and selection.
-    - three
+    - Prediction, ignoring, forgetting, and selection.
   solution: 3
 ```
 

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/conclusion.english.md

@@ -15,12 +15,13 @@ videoId: LMNub5frQi4
 
 ```yml
 question:
-  text: Question
+  text: |
+    Most people that are experts in AI or machine learning usually...:
   answers:
-    - one
+    - have one specialization.
-    - two
+    - have many specializations.
-    - three
+    - have a deep understanding of many different frameworks.
-  solution: 3
+  solution: 1
 ```
 
 </section>

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/convolutional-neural-networks-evaluating-the-model.english.md

@@ -15,11 +15,11 @@ videoId: eCATNvwraXg
 
 ```yml
 question:
-  text: Question
+  text: What is **not** a good way to increase the accuracy of a convolutional neural network?
   answers:
-    - one
+    - Augmenting the data you already have.
-    - two
+    - Using a pre-trained model.
-    - three
+    - Using your test data to retrain the model.
   solution: 3
 ```
 

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/convolutional-neural-networks-picking-a-pretrained-model.english.md

@@ -15,12 +15,36 @@ videoId: h1XUt1AgIOI
 
 ```yml
 question:
-  text: Question
+  text: |
+    Fill in the blanks below to use Google's pre-trained MobileNet V2 model as a base for a convolutional neural network:
+
+    ```py
+    base_model = tf.__A__.applications.__B__(input_shape=(160, 160, 3),
+                                                   include_top=__C__,
+                                                   weights='imagenet'
+                                                   )
+    ```
+
   answers:
-    - one
+    - |
-    - two
+      A: `keras`
-    - three
+
-  solution: 3
+      B: `MobileNetV2`
+
+      C: `False`
+    - |
+      A: `Keras`
+
+      B: `MobileNetV2`
+
+      C: `True`
+    - |
+      A: `keras`
+
+      B: `mobile_net_v2`
+
+      C: `False`
+  solution: 1
 ```
 
 </section>

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/convolutional-neural-networks-the-convolutional-layer.english.md

@@ -15,12 +15,12 @@ videoId: LrdmcQpTyLw
 
 ```yml
 question:
-  text: Question
+  text: What are the three main properties of each convolutional layer?
   answers:
-    - one
+    - Input size, the number of filters, and the sample size of the filters.
-    - two
+    - Input size, input dimensions, and the color values of the input.
-    - three
+    - Input size, input padding, and stride.
-  solution: 3
+  solution: 1
 ```
 
 </section>

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/convolutional-neural-networks.english.md

@@ -15,11 +15,12 @@ videoId: _1kTP7uoU9E
 
 ```yml
 question:
-  text: Question
+  text: |
+    Dense neural networks analyze input on a global scale and recognize patterns in specific areas. Convolutional neural networks...:
   answers:
-    - one
+    - also analyze input globally and extract features from specific areas.
-    - two
+    - do not work well for image classification or object detection.
-    - three
+    - scan through the entire input a little at a time and learn local patterns.
   solution: 3
 ```
 

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/core-learning-algorithms-building-the-model.english.md

@@ -15,12 +15,15 @@ videoId: 5wHw8BTd2ZQ
 
 ```yml
 question:
-  text: Question
+  text: What kind of estimator/model does TensorFlow recommend using for classification?
   answers:
-    - one
+    - |
-    - two
+      `LinearClassifier`
-    - three
+    - |
-  solution: 3
+      `DNNClassifier`
+    - |
+      `BoostedTreesClassifier`
+  solution: 2
 ```
 
 </section>

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/core-learning-algorithms-classification.english.md

@@ -15,12 +15,12 @@ videoId: qFF7ZQNvK9E
 
 ```yml
 question:
-  text: Question
+  text: What is classification?
   answers:
-    - one
+    - The process of separating data points into different classes.
-    - two
+    - Predicting a numeric value or forecast based on independent and dependent variables.
-    - three
+    - None of the above.
-  solution: 3
+  solution: 1
 ```
 
 </section>

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/core-learning-algorithms-clustering.english.md

@@ -15,12 +15,14 @@ videoId: 8sqIaHc9Cz4
 
 ```yml
 question:
-  text: Question
+  text: Which of the following steps is **not** part of the K-Means algorithm?
   answers:
-    - one
+    - Randomly pick K points to place K centeroids.
-    - two
+    - Assign each K point to the closest K centeroid.
-    - three
+    - Move each K centeroid into the middle of all of their data points.
-  solution: 3
+    - Shuffle the K points so they're redistributed randomly.
+    - Reassign each K point to the closest K centeroid.
+  solution: 4
 ```
 
 </section>

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/core-learning-algorithms-hidden-markov-models.english.md

@@ -15,12 +15,12 @@ videoId: IZg24y4wEPY
 
 ```yml
 question:
-  text: Question
+  text: What makes a Hidden Markov model different than linear regression or classification?
   answers:
-    - one
+    - It uses probability distributions to predict future events or states.
-    - two
+    - It analyzes the relationship between independent and dependent variables to make predictions.
-    - three
+    - It separates data points into separate categories. 
-  solution: 3
+  solution: 1
 ```
 
 </section>

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/core-learning-algorithms-the-training-process.english.md

@@ -15,12 +15,12 @@ videoId: _cEwvqVoBhI
 
 ```yml
 question:
-  text: Question
+  text: What are epochs?
   answers:
-    - one
+    - The number of times the model will see the same data.
-    - two
+    - A type of graph.
-    - three
+    - The number of elements you feed to the model at once.
-  solution: 3
+  solution: 1
 ```
 
 </section>

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/core-learning-algorithms-training-and-testing-data.english.md

@@ -15,12 +15,12 @@ videoId: wz9J1slsi7I
 
 ```yml
 question:
-  text: Question
+  text: What is categorical data?
   answers:
-    - one
+    - Another term for one-hot encoding.
-    - two
+    - Any data that is not numeric.
-    - three
+    - Any data that is represented numerically.
-  solution: 3
+  solution: 2
 ```
 
 </section>

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/core-learning-algorithms-using-probabilities-to-make-predictions.english.md

@@ -15,11 +15,14 @@ videoId: fYAYvLUawnc
 
 ```yml
 question:
-  text: Question
+  text: What TensorFlow module should you import to implement `.HiddenMarkovModel()`?
   answers:
-    - one
+    - |
-    - two
+      `tensorflow.keras`
-    - three
+    - |
+      `tensorflow_gpu`
+    - |
+      `tensorflow_probability`
   solution: 3
 ```
 

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/core-learning-algorithms-working-with-data.english.md

@@ -15,11 +15,12 @@ videoId: u85IOSsJsPI
 
 ```yml
 question:
-  text: Question
+  text: |
+    What does the pandas `.head()` function do?
   answers:
-    - one
+    - Returns the number of entries in a data frame.
-    - two
+    - Returns the number of columns in a data frame.
-    - three
+    - By default, shows the first five rows or entries in a data frame.
   solution: 3
 ```
 

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/core-learning-algorithms.english.md

@@ -15,12 +15,16 @@ videoId: u5lZURgcWnU
 
 ```yml
 question:
-  text: Question
+  text: |
+    Which type of analysis would be best suited for the following problem?: 
+    
+    You have the average temperature in the month of March for the last 100 years. Using this data, you want to predict the average temperature in the month of March 5 years from now.
   answers:
-    - one
+    - Multiple regression
-    - two
+    - Correlation
-    - three
+    - Decision tree
-  solution: 3
+    - Linear regression
+  solution: 4
 ```
 
 </section>

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/creating-a-convolutional-neural-network.english.md

@@ -15,11 +15,38 @@ videoId: kfv0K8MtkIc
 
 ```yml
 question:
-  text: Question
+  text: |
+    Fill in the blanks below to complete the architechture for a convolutional neural network:
+
+    ```py
+    model = models.__A__()
+    model.add(layers.__B__(32, (3, 3), activation='relu', input_shape=(32, 32, 3)))
+    model.add(layers.__C__(2, 2))
+    model.add(layers.__B__(64, (3, 3), activation='relu'))
+    model.add(layers.__C__(2, 2))
+    model.add(layers.__B__(32, (3, 3), activation='relu'))
+    model.add(layers.__C__(2, 2))
+    ```
+
   answers:
-    - one
+    - |
-    - two
+      A: `Sequential`
-    - three
+
+      B: `add`
+
+      C: `Wrapper`
+    - |
+      A: `keras`
+
+      B: `Cropping2D`
+
+      C: `AlphaDropout`
+    - |
+      A: `Sequential`
+
+      B: `Conv2D`
+
+      C: `MaxPooling2D`
   solution: 3
 ```
 

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/introduction-machine-learning-fundamentals.english.md

@@ -15,12 +15,13 @@ videoId: KwL1qTR5MT8
 
 ```yml
 question:
-  text: Question
+  text: |
+    Which statement below is **false**?
   answers:
-    - one
+    - Neural networks are modeled after the way the human brain works.
-    - two
+    - Computer programs that play tic-tac-toe or chess against human players are examples of simple artificial intelligence.
-    - three
+    - Machine learning is a subset of artificial intelligence.
-  solution: 3
+  solution: 1
 ```
 
 </section>

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/introduction-to-tensorflow.english.md

@@ -15,12 +15,14 @@ videoId: r9hRyGGjOgQ
 
 ```yml
 question:
-  text: Question
+  text: Which of the following is **not** a type of tensor?
   answers:
-    - one
+    - Variable
-    - two
+    - Flowing
-    - three
+    - Placeholder
-  solution: 3
+    - SparseTensor
+    - Constant
+  solution: 2
 ```
 
 </section>

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/natural-language-processing-with-rnns-building-the-model.english.md

@@ -15,11 +15,48 @@ videoId: 32WBFS7lfsw
 
 ```yml
 question:
-  text: Question
+  text: |
+    Fill in the blanks below to complete the `build_model` function:
+
+    ```py
+    def build_mode(vocab_size, embedding_dim, rnn_units, batch_size):
+        model = tf.keras.Sequential([
+            tf.keras.layers.Embedding(vocab_size,
+                                      embedding_dim, 
+                                      batch_input_shape=[batch_size, None]),
+            tf.keras.layers.__A__(rnn_units,
+                                  return_sequences=__B__,
+                                  recurrent_initializer='glorot_uniform),
+            tf.keras.layers.Dense(__C__)
+        ])
+        __D__
+    ```
+
   answers:
-    - one
+    - |
-    - two
+      A: `ELU`
-    - three
+
+      B: `True`
+
+      C: `vocab_size`
+
+      D: `return model`
+    - |
+      A: `LSTM`
+
+      B: `False`
+
+      C: `batch_size`
+
+      D: `return model`
+    - |
+      A: `LSTM`
+
+      B: `True`
+
+      C: `vocab_size`
+
+      D: `return model`
   solution: 3
 ```
 

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/natural-language-processing-with-rnns-create-a-play-generator.english.md

@@ -15,12 +15,28 @@ videoId: j5xsxjq_Xk8
 
 ```yml
 question:
-  text: Question
+  text: |
+
+    Fill in the blanks below to create the training examples for the RNN:
+
+    ```py
+    char_dataset = tf.data.__A__.__B__(text_as_int)
+    ```
+
   answers:
-    - one
+    - |
-    - two
+      A: `DataSet`
-    - three
+
-  solution: 3
+      B: `from_tensor_slices`
+    - |
+      A: `data`
+
+      B: `from_tensors`
+    - |
+      A: `DataSet`
+
+      B: `from_generator`
+  solution: 1
 ```
 
 </section>

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/natural-language-processing-with-rnns-making-predictions.english.md

@@ -15,12 +15,13 @@ videoId: WO1hINnBj20
 
 ```yml
 question:
-  text: Question
+  text: |
+    Before you make a prediction with your own review, you should...:
   answers:
-    - one
+    - decode the training dataset and compare the results to the test data.
-    - two
+    - use the encodings from the training dataset to encode your review.
-    - three
+    - assign random values between 0 and the maximum number of vocabulary in your dataset to each word in your review.
-  solution: 3
+  solution: 2
 ```
 
 </section>

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/natural-language-processing-with-rnns-part-2.english.md

@@ -15,11 +15,12 @@ videoId: mUU9YXOFbZg
 
 ```yml
 question:
-  text: Question
+  text: |
+    Word embeddings are...:
   answers:
-    - one
+    - an unordered group of encoded words that describes the frequency of words in a given document.
-    - two
+    - a group of encoded words that preserves the original order of the words in a given document.
-    - three
+    - a vectorized representation of words in a given document that places words with similar meanings near each other.
   solution: 3
 ```
 

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/natural-language-processing-with-rnns-recurring-neural-networks.english.md

@@ -15,12 +15,17 @@ videoId: bX5681NPOcA
 
 ```yml
 question:
-  text: Question
+  text: What is true about Recurrent Neural Networks?
   answers:
-    - one
+    - |
-    - two
+      1: They are a type of feed-forward neural network.
-    - three
+    - |
-  solution: 3
+      2: They maintain an internal memory/state of the input that was already processed.
+    - |
+      3: RNN's contain a loop and process one piece of input at a time.
+    - |
+      4: Both 2 and 3.
+  solution: 4
 ```
 
 </section>

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/natural-language-processing-with-rnns-sentimental-analysis.english.md

@@ -15,11 +15,36 @@ videoId: lYeLtu8Nq7c
 
 ```yml
 question:
-  text: Question
+  text: |
+    Fill in the blanks below to create the model for the RNN:
+
+    ```py
+    model = __A__.keras.Sequential([
+        __A__.keras.layers.__B__(88584, 32),
+        __A__.keras.layers.__C__(32),
+        __A__.keras.layers.DENSE(1, activation='sigmoid')
+    ])
+    ```
+
   answers:
-    - one
+    - |
-    - two
+      A: `tensor_flow`
-    - three
+
+      B: `embedding`
+
+      C: `LSTM`
+    - |
+      A: `tf`
+
+      B: `Embedding`
+
+      C: `AlphaDropout`
+    - |
+      A: `tf`
+
+      B: `Embedding`
+
+      C: `LSTM`
   solution: 3
 ```
 

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/natural-language-processing-with-rnns-training-the-model.english.md

@@ -15,12 +15,41 @@ videoId: hEUiK7j9UI8
 
 ```yml
 question:
-  text: Question
+  text: |
+    Fill in the blanks below to save your model's checkpoints in the `./checkpoints` directory and call the latest checkpoint for training:
+
+    ```py
+    checkpoint_dir = __A__
+    checkpoint_prefix = os.path.join(checkpoint_dir, 'ckpt_{epoch}')
+
+    checkpoint_callback = tf.keras.callbacks.__B__(
+        filepath=checkpoint_prefix,
+        save_weights_only=True
+    )
+
+    history = model.fit(data, epochs=2, callbacks=[__C__])
+    ```
+
   answers:
-    - one
+    - |
-    - two
+      A: `'./training_checkpoints'`
-    - three
+
-  solution: 3
+      B: `ModelCheckpoint`
+
+      C: `checkpoint_prefix`
+    - |
+      A: `'./checkpoints'`
+
+      B: `ModelCheckpoint`
+
+      C: `checkpoint_callback`
+    - |
+      A: `'./checkpoints'`
+
+      B: `BaseLogger`
+
+      C: `checkpoint_callback`
+  solution: 2
 ```
 
 </section>

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/natural-language-processing-with-rnns.english.md

@@ -15,12 +15,13 @@ videoId: ZyCaF5S-lKg
 
 ```yml
 question:
-  text: Question
+  text: |
+    Natural Language Processing is a branch of artifitial intelligence that...:
   answers:
-    - one
+    - deals with how computers understand and process natural/human languages.
-    - two
+    - translates image data into natural/human languages.
-    - three
+    - is focused on translating computer languages into natural/human languages.
-  solution: 3
+  solution: 1
 ```
 
 </section>

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/neural-networks-activation-functions.english.md

@@ -15,12 +15,12 @@ videoId: S45tqW6BqRs
 
 ```yml
 question:
-  text: Question
+  text: Which activation function switches values between -1 and 1?
   answers:
-    - one
+    - Relu (Rectified Linear Unit)
-    - two
+    - Tanh (Hyperbolic Tangent)
-    - three
+    - Sigmoid
-  solution: 3
+  solution: 2
 ```
 
 </section>

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/neural-networks-creating-a-model.english.md

@@ -15,12 +15,37 @@ videoId: K8bz1bmOCTw
 
 ```yml
 question:
-  text: Question
+  text: |
+    Fill in the blanks below to build a sequential model of dense layers:
+
+    ```py
+    model = __A__.__B__([
+        __A__.layers.Flatten(input_shape=(28, 28)),
+        __A__.layers.__C__(128, activation='relu'),
+        __A__.layers.__C__(10, activation='softmax')
+    ])
+    ```
+
   answers:
-    - one
+    - |
-    - two
+      A: `keras`
-    - three
+      
-  solution: 3
+      B: `Sequential`
+      
+      C: `Dense`
+    - |
+      A: `tf`
+      
+      B: `Sequential`
+      
+      C: `Categorical`
+    - |
+      A: `keras`
+      
+      B: `sequential`
+      
+      C: `dense`
+  solution: 1
 ```
 
 </section>

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/neural-networks-optimizers.english.md

@@ -15,12 +15,12 @@ videoId: hdOtRPQe1o4
 
 ```yml
 question:
-  text: Question
+  text: What is an optimizer function?
   answers:
-    - one
+    - A function that increases the accuracy of a model's predictions.
-    - two
+    - A function that implements the gradient descent and backpropogation algorithms for you.
-    - three
+    - A function that reduces the time a model needs to train.
-  solution: 3
+  solution: 2
 ```
 
 </section>

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/neural-networks-with-tensorflow.english.md

@@ -15,11 +15,12 @@ videoId: uisdfrNrZW4
 
 ```yml
 question:
-  text: Question
+  text: |
+    A densely connected neural network is one in which...:
   answers:
-    - one
+    - all the neurons in the current layer are connected to one neuron in the previous layer.
-    - two
+    - all the neurons in each layer are connected randomly.
-    - three
+    - all the neurons in the current layer are connected to every neuron in the previous layer.
   solution: 3
 ```
 

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/reinforcement-learning-with-q-learning-example.english.md

@@ -15,12 +15,33 @@ videoId: RBBSNta234s
 
 ```yml
 question:
-  text: Question
+  text: |
+    Fill in the blanks to complete the following Q-Learning equation:
+
+    ```py
+    Q[__A__, __B__] = Q[__A__, __B__] + LEARNING_RATE * (reward + GAMMA * np.max(Q[__C__, :]) - Q[__A__, __B__])
+    ```
+
   answers:
-    - one
+    - |
-    - two
+      A: `state`
-    - three
+
-  solution: 3
+      B: `action`
+
+      C: `next_state`
+    - |
+      A: `state`
+
+      B: `action`
+
+      C: `prev_state`
+    - |
+      A: `state`
+
+      B: `reaction`
+
+      C: `next_state`
+  solution: 1
 ```
 
 </section>

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/reinforcement-learning-with-q-learning-part-2.english.md

@@ -15,12 +15,11 @@ videoId: DX7hJuaUZ7o
 
 ```yml
 question:
-  text: Question
+  text: What can happen if the agent does not have a good balance of taking random actions and using learned actions?
   answers:
-    - one
+    - The agent will always try to minimize its reward for the current state/action, leading to local minima.
-    - two
+    - The agent will always try to maximize its reward for the current state/action, leading to local maxima.
-    - three
+  solution: 2
-  solution: 3
 ```
 
 </section>

curriculum/challenges/english/11-machine-learning-with-python/tensorflow/reinforcement-learning-with-q-learning.english.md

@@ -15,12 +15,12 @@ videoId: Cf7DSU0gVb4
 
 ```yml
 question:
-  text: Question
+  text: The key components of reinforcement learning are...
   answers:
-    - one
+    - environment, representative, state, reaction, and reward.
-    - two
+    - environment, agent, state, action, and reward.
-    - three
+    - habitat, agent, state, action, and punishment.
-  solution: 3
+  solution: 2
 ```
 
 </section>