Fix typos

01_materials/slides/10_numpy.ipynb

@@ -239,7 +239,7 @@
       },
       "outputs": [],
       "source": [
-        "# create a 1D array from 1 til 10 in steps of 2\n",
+        "# create a 1D array from 1 until 10 in steps of 2\n",
         "np.arange(1, 10, 2)"
       ]
     },
@@ -1163,7 +1163,7 @@
       "source": [
         "## Logic and filtering\n",
         "\n",
-        "`numpy` arrays work with boolean expressions. Each element is checked, and the result is an array of `True`/`False` values. They resulting arrays sometimes called _masks_ because they are used to mask, or filter, data."
+        "`numpy` arrays work with Boolean expressions. Each element is checked, and the result is an array of `True`/`False` values. They resulting arrays sometimes called _masks_ because they are used to mask, or filter, data."
       ]
     },
     {
@@ -1231,7 +1231,7 @@
         "id": "bae12ead"
       },
       "source": [
-        "To filter use a boolean expression as a mask, pass it into square brackets after the array to mask."
+        "To filter use a Boolean expression as a mask, pass it into square brackets after the array to mask."
       ]
     },
     {
@@ -1299,7 +1299,7 @@
         "id": "cb4a4676"
       },
       "source": [
-        "We can even use masks to generate new arrays with conditionals. `np.where()` takes as its arguments a boolean expression, an expression to evaluate if `True`, and an expression to evaluate elsewise. This is analagous to creating a new array based on an old one with a `for` loop and `if`/`else` statements, but much faster."
+        "We can even use masks to generate new arrays with conditionals. `np.where()` takes as its arguments a Boolean expression, an expression to evaluate if `True`, and an expression to evaluate elsewise. This is analogous to creating a new array based on an old one with a `for` loop and `if`/`else` statements, but much faster."
       ]
     },
     {