diff --git a/Problem1.py b/Problem1.py
new file mode 100644
index 00000000..fbd37c75
--- /dev/null
+++ b/Problem1.py
@@ -0,0 +1,43 @@
+#Find First and Last Position of Element in Sorted Array
+# Time complexity O(logn) 
+
+class Solution:
+    def searchRange(self, nums: List[int], target: int) -> List[int]:
+        #1st using binary array search for the starting index
+
+        left = 0
+        right = len(nums) - 1
+        leftIndex = -1
+        rightIndex = -1
+        while left <= right:
+            mid = left + (right-left)//2
+            if target == nums[mid]:
+                if mid == left or target != nums[mid-1]:
+                    leftIndex = mid
+                    break
+            if target > nums[mid]:
+                left = mid+1
+            else:
+                right = mid - 1
+        
+
+        # if leftindex does not get updated, menas target is not present return [-1,-1]
+        if leftIndex == -1:
+            return [leftIndex, rightIndex]
+        #then using the binary search starting from the left index, the mid can point either to same or bigger number
+        left = leftIndex
+        right = len(nums) - 1
+        while left <= right:
+            mid = left + (right-left)//2
+
+            # if mid is pointing to same number move the left index ahead
+            if target == nums[mid]:
+                if mid==right or nums[mid+1] != target:
+                    rightIndex = mid
+                    break
+                left = mid+1
+            else:
+                right = mid - 1
+        
+
+        return [leftIndex, rightIndex]
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diff --git a/Problem2.py b/Problem2.py
new file mode 100644
index 00000000..9d456855
--- /dev/null
+++ b/Problem2.py
@@ -0,0 +1,27 @@
+#Find Minimum in Rotated Sorted Array
+
+class Solution:
+    def findMin(self, nums: List[int]) -> int:
+        # in case of rotated array the lowest will always lie in unsorted part
+        # in case both parts are sorted then the smallest item will be on the left most element
+
+        left = 0
+        right = len(nums) - 1
+        
+        while left <= right:
+            mid = left + (right-left)//2
+            #if both side elemnts of the mid are bigger means the mid is lowest point
+            #in case of boundary elements if the other isde is bigger than also it is smallest
+
+            val = nums[mid]
+            if (mid  == 0 or val < nums[mid-1]) and (mid == len(nums)-1 or val < nums[mid+1]):
+                return val
+            
+            if nums[right] >  nums[mid]:
+                #right subarray is sorted, min will lie in left subarray
+                right = mid-1
+            else:
+                left = mid+1
+        
+        # return anything as the code won't reach here
+        return -1
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diff --git a/Problem3.py b/Problem3.py
new file mode 100644
index 00000000..8736560e
--- /dev/null
+++ b/Problem3.py
@@ -0,0 +1,22 @@
+#Find Peak Element
+
+class Solution:
+    def findPeakElement(self, nums: List[int]) -> int:
+        left = 0
+        right = len(nums) - 1
+
+        while left <= right:
+            mid  = left + (right-left)//2
+            val = nums[mid]
+            # if peak return index
+            if (mid==0 or val > nums[mid-1]) and (mid == len(nums)-1 or val > nums[mid+1]):
+                return mid
+            
+            # else move towards a peak by moving towards increasing number
+            if mid > 0 and nums[mid-1]>val:
+                right = mid-1
+            else:
+                left = mid+1
+
+        # return anything as the code won't reach here
+        return -1
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