diff --git a/intermediate/Searching_Algorithm/Binary_Seach.py b/intermediate/Searching_Algorithm/Binary_Seach.py
new file mode 100644
index 0000000..e386de0
--- /dev/null
+++ b/intermediate/Searching_Algorithm/Binary_Seach.py
@@ -0,0 +1,131 @@
+"""
+Title: Binary Search - Tutorial and Examples
+Author: Python-Basics-to-Advanced Contributors
+Difficulty: Intermediate
+Description: Iterative and recursive implementations of binary search with examples,
+             doctests, performance comparison, and practice exercises.
+Date: October 2025
+"""
+
+print("=== Binary Search Tutorial ===\n")
+
+print("Binary search finds an item in a sorted list in O(log n) time.")
+print("We'll provide both iterative and recursive implementations, plus examples.")
+
+# =============================================================================
+# Iterative Binary Search
+# =============================================================================
+
+def binary_search_iterative(arr, key):
+    """Return the index of key in sorted list arr or -1 if not found.
+
+    Args:
+        arr (list): Sorted list of comparable items.
+        key: Item to search for.
+
+    Returns:
+        int: Index of key in arr, or -1 if key is not present.
+    """
+    low = 0
+    high = len(arr) - 1
+
+    while low <= high:
+        mid = (low + high) // 2
+        if arr[mid] < key:
+            low = mid + 1
+        elif arr[mid] > key:
+            high = mid - 1
+        else:
+            return mid
+    return -1
+
+
+# =============================================================================
+# Recursive Binary Search
+# =============================================================================
+
+def binary_search_recursive(arr, key, low=0, high=None):
+    """Recursive binary search wrapper. Returns index of key or -1.
+
+    This function is a small wrapper so callers can pass only arr and key.
+    """
+    if high is None:
+        high = len(arr) - 1
+
+    if low > high:
+        return -1
+
+    mid = (low + high) // 2
+    if arr[mid] == key:
+        return mid
+    elif arr[mid] < key:
+        return binary_search_recursive(arr, key, mid + 1, high)
+    else:
+        return binary_search_recursive(arr, key, low, mid - 1)
+
+
+# =============================================================================
+# Examples and doctest-like checks
+# =============================================================================
+
+example_list = [10, 20, 30, 40, 50]
+print(f"Example list: {example_list}")
+
+print("Iterative search for 40 -> expected index 3:")
+print(binary_search_iterative(example_list, 40))
+
+print("Recursive search for 40 -> expected index 3:")
+print(binary_search_recursive(example_list, 40))
+
+print("Search for missing value 25 -> expected -1:")
+print(binary_search_iterative(example_list, 25))
+
+# Edge cases
+print("Edge cases:")
+print("Empty list:", binary_search_iterative([], 1))
+print("Single-element found:", binary_search_iterative([5], 5))
+print("Single-element missing:", binary_search_iterative([5], 3))
+
+
+# =============================================================================
+# Performance comparison (small micro-benchmark)
+# =============================================================================
+
+import time
+
+large_range = list(range(1000000))  # 1M items
+key_present = 999999
+key_absent = -1
+
+start = time.time()
+res = binary_search_iterative(large_range, key_present)
+iter_time_present = time.time() - start
+
+start = time.time()
+res_rec = binary_search_recursive(large_range, key_present)
+rec_time_present = time.time() - start
+
+print(f"\nPerformance (searching present key): iterative={iter_time_present:.6f}s, recursive={rec_time_present:.6f}s")
+
+start = time.time()
+res = binary_search_iterative(large_range, key_absent)
+iter_time_absent = time.time() - start
+
+start = time.time()
+res_rec = binary_search_recursive(large_range, key_absent)
+rec_time_absent = time.time() - start
+
+print(f"Performance (searching absent key): iterative={iter_time_absent:.6f}s, recursive={rec_time_absent:.6f}s")
+
+
+# =============================================================================
+# Practice exercises
+# =============================================================================
+
+print("\n--- Practice Exercises ---")
+print("1. Modify binary search to return the insertion index (like bisect_left).")
+print("2. Adapt binary search to work with a list of tuples sorted by the first element.")
+print("3. Implement an iterative binary search that returns the first occurrence in a list with duplicates.")
+
+print("\n--- End of Tutorial ---")
+print("Binary search implementations and micro-benchmarks complete.")
\ No newline at end of file
diff --git a/intermediate/Searching_Algorithm/Exponential_Search.py b/intermediate/Searching_Algorithm/Exponential_Search.py
new file mode 100644
index 0000000..11c6ddf
--- /dev/null
+++ b/intermediate/Searching_Algorithm/Exponential_Search.py
@@ -0,0 +1,78 @@
+"""
+Title: Additional Search Algorithms - Tutorial and Examples
+Author: Python-Basics-to-Advanced Contributors
+Difficulty: Intermediate
+Description: Implementations and example of exponential search. Includes simple
+             micro-benchmarks and practice exercises.
+Date: October 2025
+"""
+
+print("=== Additional Search Algorithms Tutorial ===\n")
+
+print("This module contains Exponential algorithms beyond binary search:")
+print("Exponential search\n")
+
+# =============================================================================
+# Exponential Search
+# =============================================================================
+
+def exponential_search(arr, key):
+    """Exponential search for sorted arrays. Returns index or -1."""
+    n = len(arr)
+    if n == 0:
+        return -1
+    if arr[0] == key:
+        return 0
+    # Find range for binary search by repeated doubling
+    i = 1
+    while i < n and arr[i] <= key:
+        i *= 2
+    # Binary search on the found range
+    low = i // 2
+    high = min(i, n - 1)
+
+    # Reuse the iterative binary search
+    def _bin_search(subarr, key, offset):
+        l = 0
+        h = len(subarr) - 1
+        while l <= h:
+            m = (l + h) // 2
+            if subarr[m] < key:
+                l = m + 1
+            elif subarr[m] > key:
+                h = m - 1
+            else:
+                return offset + m
+        return -1
+
+    return _bin_search(arr[low:high+1], key, low)
+
+
+# =============================================================================
+# Examples and micro-benchmark
+# =============================================================================
+
+if __name__ == "__main__":
+    example = [i for i in range(0, 1000, 2)]  # even numbers 0..998
+    keys = [0, 250, 999, -1]
+
+    print("Example array: first 10 ->", example[:10])
+
+    for k in keys:
+        print(f"\nSearching for {k}:")
+        print("expo_search   ->", exponential_search(example, k))
+
+    # Simple micro-benchmark comparing linear and binary (via exponential's bin part)
+    import time
+
+    large = list(range(1000000))
+    target = 999999
+
+    start = time.perf_counter()
+    lin_time = time.perf_counter() - start
+
+    start = time.perf_counter()
+    res_exp = exponential_search(large, target)
+    exp_time = time.perf_counter() - start
+
+    print(f"\nMicro-benchmark (searching present key={target}): linear={lin_time:.6f}s, exponential(binary)={exp_time:.6f}s")