diff --git a/lectures/18_trees_I/README.md b/lectures/18_trees_I/README.md
index 48024ce..c1a6f12 100644
--- a/lectures/18_trees_I/README.md
+++ b/lectures/18_trees_I/README.md
@@ -1,6 +1,6 @@
-# Lecture 17 --- Trees, Part I
+# Lecture 18 --- Trees, Part I
 
-## Review from Lecture 16
+## Review from Lecture 17
 
 - STL set container class (like STL map, but without the pairs!)
 - set iterators, insert, erase, find
@@ -16,7 +16,7 @@
 - Binary search trees are the mechanism underlying maps & sets (and multimaps & multisets).
 - Mathematically speaking: A _graph_ is a set of vertices connected by edges. And a tree is a special graph that has no _cycles_. The edges that connect nodes in trees and graphs may be _directed_ or _undirected_.
 
-## 17.1 Definition: Binary Trees
+## 18.1 Definition: Binary Trees
 
 - A binary tree (strictly speaking, a “rooted binary
 tree”) is either empty or is a node that has
@@ -42,7 +42,7 @@ called a leaf node.
 - A node’s parent is the unique node that points to
 it. Only the root has no parent.
 
-## 17.2 Definition: Binary Search Trees
+## 18.2 Definition: Binary Search Trees
 
 - A binary search tree (often abbreviated to
 BST) is a binary tree where at each node
@@ -58,7 +58,7 @@ storing string values.
 
 ![alt text](bst.png "binary search tree")
 
-## 17.3 Definition: Balanced Trees
+## 18.3 Definition: Balanced Trees
 
 - The number of nodes on each subtree of each node in a
 “balanced” tree is approximately the same. In order to
@@ -67,7 +67,7 @@ about the number of nodes in the tree?
 - In order to claim the performance advantages of trees, we must assume and ensure that our data structure
 remains approximately balanced. (You’ll see much more of this in Intro to Algorithms!)
 
-## 17.4 Exercise
+## 18.4 Exercise
 
 Consider the following values:
 4.5, 9.8, 3.5, 13.6, 19.2, 7.4, 11.7
@@ -80,7 +80,7 @@ tree structure for a given set of values is not unique!
 3. How many exactly balanced binary search trees exist with these numbers? How many exactly balanced
 binary trees exist with these numbers?
 
-## 17.5 Beginning our implementation of ds_set: The Tree Node Class
+## 18.5 Beginning our implementation of ds_set: The Tree Node Class
 
 - Here is the class definition for nodes in the tree. We will use this for the tree manipulation code we write.
 
@@ -99,7 +99,7 @@ public:
 
   ![alt text](ds_set_diagram.png "ds set diagram")
 
-## 17.6 Exercises
+## 18.6 Exercises
 
 1. Write a templated function to find the smallest value stored in a binary search tree whose root node is pointed
 to by p.
@@ -108,7 +108,7 @@ to by p.
 tree) of integers. The function should accept a TreeNode<int> pointer as its sole argument and return an
 integer. Hint: think recursively!
 
-## 17.7 ds_set and Binary Search Tree Implementation
+## 18.7 ds_set and Binary Search Tree Implementation
 
 - A partial implementation of a set using a binary search tree is provided in this [ds_set_starter.h](ds_set_starter.h). We will continue to study this implementation in Lab 10 & the next lecture.
 - The increment and decrement operations for iterators have been omitted from this implementation. Next week
@@ -116,7 +116,7 @@ in lecture we will discuss a couple strategies for adding these operations.
 - We will use this as the basis both for understanding an initial selection of tree algorithms and for thinking
 about how standard library sets really work.
 
-## 17.8 ds_set: Class Overview
+## 18.8 ds_set: Class Overview
 
 - There is two auxiliary classes, TreeNode and tree_iterator. All three classes are templated.
 - The only member variables of the ds_set class are the root and the size (number of tree nodes).
@@ -130,7 +130,7 @@ node) that does all of the work.
 - Because the class stores and manages dynamically allocated memory, a copy constructor, operator=, and
 destructor must be provided.
 
-## 17.9 Exercises
+## 18.9 Exercises
 
 1. Provide the implementation of the member function ds_set<T>::begin. This is essentially the problem of
 finding the node in the tree that stores the smallest value.