diff --git a/contains-duplicate/wlghsp.py b/contains-duplicate/wlghsp.py
new file mode 100644
index 0000000000..7f23dd94f5
--- /dev/null
+++ b/contains-duplicate/wlghsp.py
@@ -0,0 +1,7 @@
+"""
+ * Time Complexity: O(N)
+ * Space Complexity: O(N)
+"""
+class Solution:
+    def containsDuplicate(self, nums: list[int]) -> bool:
+        return len(set(nums)) != len(nums)
diff --git a/house-robber/wlghsp.py b/house-robber/wlghsp.py
new file mode 100644
index 0000000000..6d46f94cb0
--- /dev/null
+++ b/house-robber/wlghsp.py
@@ -0,0 +1,20 @@
+"""
+ * Time Complexity: O(N)
+ * Space Complexity: O(N)
+"""
+class Solution:
+    def rob(self, nums: list[int]) -> int:
+        n = len(nums)
+
+        if n == 1:
+            return nums[0]
+        
+        # dp[i]: 0번 부터 i번째 집까지 고려했을 때 얻을 수 있는 최대 금액
+        dp = [0] * n
+        dp[0] = nums[0]
+        dp[1] = max(nums[0], nums[1])
+
+        for i in range(2, n):
+            dp[i] = max(dp[i - 2] + nums[i], dp[i - 1])
+
+        return dp[-1]
diff --git a/longest-consecutive-sequence/wlghsp.py b/longest-consecutive-sequence/wlghsp.py
new file mode 100644
index 0000000000..273a5f2825
--- /dev/null
+++ b/longest-consecutive-sequence/wlghsp.py
@@ -0,0 +1,15 @@
+"""
+ * Time Complexity: O(N)
+ * Space Complexity: O(N)
+"""
+class Solution:
+    def longestConsecutive(self, nums: list[int]) -> int:
+        nums_set = set(nums)
+        ans = 0
+        for n in nums_set:
+            if (n - 1) not in nums_set:
+                length = 1
+                while n + length in nums_set:
+                    length += 1
+                ans = max(length, ans)
+        return ans
diff --git a/top-k-frequent-elements/wlghsp.py b/top-k-frequent-elements/wlghsp.py
new file mode 100644
index 0000000000..75edb6a64a
--- /dev/null
+++ b/top-k-frequent-elements/wlghsp.py
@@ -0,0 +1,24 @@
+"""
+ * Time Complexity: O(n)
+ * Space Complexity: O(n)
+"""
+from collections import Counter
+class Solution:
+    def topKFrequent(self, nums: list[int], k: int) -> list[int]:
+        # 1. 빈도 계산: O(N)
+        count = Counter(nums)
+
+        # 2. 빈도를 인덱스로 사용하는 버킷 배열 생성: O(N)
+        # 최대 빈도는 len(nums)이므로 크기는 len(nums) + 1
+        buckets = [[] for _ in range(len(nums) + 1)]
+        for num, freq in count.items():
+            buckets[freq].append(num)
+
+        # 3. 높은 빈도(뒤쪽 인덱스)부터 k개 추출: O(N)
+        res = []
+        for freq in range(len(buckets) - 1, 0, -1):
+            for num in buckets[freq]:
+                res.append(num)
+                if len(res) == k:
+                    return res
+        return res
diff --git a/two-sum/wlghsp.py b/two-sum/wlghsp.py
new file mode 100644
index 0000000000..cbdd3fb7d3
--- /dev/null
+++ b/two-sum/wlghsp.py
@@ -0,0 +1,13 @@
+"""
+ * Time Complexity: O(N)
+ * Space Complexity: O(N)
+"""
+class Solution:
+    def twoSum(self, nums: list[int], target: int) -> list[int]:
+        num_dict = {}
+        for i, e in enumerate(nums):
+            other = target - e
+            if other in num_dict:
+                return [num_dict[other], i]
+            num_dict[e] = i
+        return []