diff --git a/02_activities/assignments/assignment_1.ipynb b/02_activities/assignments/assignment_1.ipynb
index bee48d5a0..05e2de427 100644
--- a/02_activities/assignments/assignment_1.ipynb
+++ b/02_activities/assignments/assignment_1.ipynb
@@ -56,13 +56,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# For testing purposes, we will write our code in the function\n",
     "def anagram_checker(word_a, word_b):\n",
-    "  # Your code here\n",
+    "    a_norm = \"\".join(ch.lower() for ch in word_a if ch.isalpha())\n",
+    "    b_norm = \"\".join(ch.lower() for ch in word_b if ch.isalpha())\n",
+    "    return sorted(a_norm) == sorted(b_norm)\n",
     "\n",
     "# Run your code to check using the words below:\n",
     "anagram_checker(\"Silent\", \"listen\")"
@@ -70,18 +83,40 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "False"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "anagram_checker(\"Silent\", \"Night\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "anagram_checker(\"night\", \"Thing\")"
    ]
@@ -97,12 +132,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
     "def anagram_checker(word_a, word_b, is_case_sensitive):\n",
-    "  # Modify your existing code here\n",
+    "    def normalize(s):\n",
+    "        s = \"\".join(ch for ch in s if ch.isalpha())\n",
+    "        return s if is_case_sensitive else s.lower()\n",
     "\n",
     "# Run your code to check using the words below:\n",
     "anagram_checker(\"Silent\", \"listen\", False) # True"
@@ -110,7 +147,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -130,7 +167,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "new-learner",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -144,7 +181,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.8"
+   "version": "3.9.6"
   }
  },
  "nbformat": 4,
diff --git a/02_activities/assignments/assignment_2.ipynb b/02_activities/assignments/assignment_2.ipynb
index 36a3e2bb7..ded15a5d9 100644
--- a/02_activities/assignments/assignment_2.ipynb
+++ b/02_activities/assignments/assignment_2.ipynb
@@ -72,11 +72,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {
     "id": "n0m48JsS-nMC"
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0,0,1,3,1,2,4,7,8,3,3,3,10,5,7,4,7,7,12,18,6,13,11,11,7,7,4,6,8,8,4,4,5,7,3,4,2,3,0,0\n",
+      "0,1,2,1,2,1,3,2,2,6,10,11,5,9,4,4,7,16,8,6,18,4,12,5,12,7,11,5,11,3,3,5,4,4,5,5,1,1,0,1\n",
+      "0,1,1,3,3,2,6,2,5,9,5,7,4,5,4,15,5,11,9,10,19,14,12,17,7,12,11,7,4,2,10,5,4,2,2,3,2,2,1,1\n",
+      "0,0,2,0,4,2,2,1,6,7,10,7,9,13,8,8,15,10,10,7,17,4,4,7,6,15,6,4,9,11,3,5,6,3,3,4,2,3,2,1\n",
+      "0,1,1,3,3,1,3,5,2,4,4,7,6,5,3,10,8,10,6,17,9,14,9,7,13,9,12,6,7,7,9,6,3,2,2,4,2,0,1,1\n",
+      "0,0,1,2,2,4,2,1,6,4,7,6,6,9,9,15,4,16,18,12,12,5,18,9,5,3,10,3,12,7,8,4,7,3,5,4,4,3,2,1\n",
+      "0,0,2,2,4,2,2,5,5,8,6,5,11,9,4,13,5,12,10,6,9,17,15,8,9,3,13,7,8,2,8,8,4,2,3,5,4,1,1,1\n",
+      "0,0,1,2,3,1,2,3,5,3,7,8,8,5,10,9,15,11,18,19,20,8,5,13,15,10,6,10,6,7,4,9,3,5,2,5,3,2,2,1\n",
+      "0,0,0,3,1,5,6,5,5,8,2,4,11,12,10,11,9,10,17,11,6,16,12,6,8,14,6,13,10,11,4,6,4,7,6,3,2,1,0,0\n",
+      "0,1,1,2,1,3,5,3,5,8,6,8,12,5,13,6,13,8,16,8,18,15,16,14,12,7,3,8,9,11,2,5,4,5,1,4,1,2,0,0\n"
+     ]
+    }
+   ],
    "source": [
     "all_paths = [\n",
     "  \"../../05_src/data/assignment_2_data/inflammation_01.csv\",\n",
@@ -94,9 +111,9 @@
     "]\n",
     "\n",
     "with open(all_paths[0], 'r') as f:\n",
-    "    # YOUR CODE HERE: Use the readline() or readlines() method to read the .csv file into a variable\n",
-    "    \n",
-    "    # YOUR CODE HERE: Iterate through the variable using a for loop and print each row for inspection"
+    "    rows = f.readlines()              \n",
+    "    for line in rows[:10]:           \n",
+    "        print(line.strip())"
    ]
   },
   {
@@ -130,7 +147,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {
     "id": "82-bk4CBB1w4"
    },
@@ -144,16 +161,12 @@
     "\n",
     "    # Implement the specific operation based on the 'operation' argument\n",
     "    if operation == 'mean':\n",
-    "        # YOUR CODE HERE: Calculate the mean (average) number of flare-ups for each patient\n",
-    "\n",
+    "        summary_values = np.mean(data, axis=ax)\n",
     "    elif operation == 'max':\n",
-    "        # YOUR CODE HERE: Calculate the maximum number of flare-ups experienced by each patient\n",
-    "\n",
+    "        summary_values = np.max(data, axis=ax)\n",
     "    elif operation == 'min':\n",
-    "        # YOUR CODE HERE: Calculate the minimum number of flare-ups experienced by each patient\n",
-    "\n",
+    "        summary_values = np.min(data, axis=ax)\n",
     "    else:\n",
-    "        # If the operation is not one of the expected values, raise an error\n",
     "        raise ValueError(\"Invalid operation. Please choose 'mean', 'max', or 'min'.\")\n",
     "\n",
     "    return summary_values"
@@ -161,11 +174,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {
     "id": "3TYo0-1SDLrd"
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "60\n"
+     ]
+    }
+   ],
    "source": [
     "# Test it out on the data file we read in and make sure the size is what we expect i.e., 60\n",
     "# Your output for the first file should be 60\n",
@@ -228,7 +249,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {
     "id": "_svDiRkdIwiT"
    },
@@ -251,7 +272,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {
     "id": "LEYPM5v4JT0i"
    },
@@ -260,16 +281,23 @@
     "# Define your function `detect_problems` here\n",
     "\n",
     "def detect_problems(file_path):\n",
-    "  #YOUR CODE HERE: Use patient_summary() to get the means and check_zeros() to check for zeros in the means\n",
-    "\n",
-    "  return"
+    "    means = patient_summary(file_path, 'mean')\n",
+    "    return check_zeros(means)\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "False\n"
+     ]
+    }
+   ],
    "source": [
     "# Test out your code here\n",
     "# Your output for the first file should be False\n",
@@ -327,7 +355,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.8"
+   "version": "3.9.6"
   }
  },
  "nbformat": 4,