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Lectures

This table contains links to the lecture slides.
# DATE SLIDES SECTION DEMOS
The lectures below have not yet been updated for Fall 2025.
1 Tuesday
9/2		  Introduction  
 Union–Find  
1.5
 Quick-union
Weighted quick-union
2 Thursday
9/4		  Analysis of Algorithms  
1.4
 –
3 Tuesday
9/9		  Stacks and Queues I:
Resizable Arrays  
1.3
 Function-call stack
Resizable-array queue
4 Thursday
9/11		  Stacks and Queues II:
Linked Lists  
1.3
 –
5 Tuesday
9/16		  Elementary Sorts  
2.1
 Selection sort
Insertion sort
Binary search
6 Thursday
9/18		  Mergesort  
2.2
 Merging
7 Tuesday
9/23		  Quicksort  
2.3
 Quicksort
2-way partitioning
3-way partitioning
Quickselect
8 Thursday
9/25		  Priority Queues  
2.4
 Heap operations
9 Tuesday
9/30		  Elementary Symbol Tables  
 BSTs  
3.1
3.2
 BST operations
10 Thursday
10/2		  Balanced Search Trees  
3.3
 2–3 trees
Red–black BSTs
11 Tuesday
10/7		  Midterm Exam 
–
 –
12 Thursday
10/9		  no lecture 
–
 –
13 Tuesday
10/21		  Geometric Applications of BSTs  
–
 Line segment intersection
K-d trees
14 Thursday
10/23		  Hash Tables  
3.4
 Linear probing
15 Tuesday
10/28		  Graphs and Digraphs I  
4.1
4.2
 Directed DFS
Directed paths
Undirected DFS
16 Thursday
10/30		  Graphs and Digraphs II  
4.1
4.2
 Directed BFS
Topological sort
17 Tuesday
11/4		  Minimum Spanning Trees  
4.3
 Kruskal
Prim
18 Thursday
11/6		  Shortest Paths  
4.4
 Bellman–Ford
Dijkstra
19 Tuesday
11/11		  Dynamic Programming  
–
 readings
20 Thursday
11/13		  Maxflows and Mincuts  
6.4
 Ford–Fulkerson
21 Tuesday
11/18		  Multiplicative Weights  
–
 –
22 Thursday
11/20		  Randomness  
–
 Knuth shuffle
Karger
23 Tuesday
12/2		  Intractability  
–
 –
24 Thursday
12/4		  Algorithm Design  
–
 –


Readings. All readings refer to Algorithms, 4th edition by R. Sedgewick and K. Wayne unless otherwise specified.

Advice. In general, slides are intended for the lecture presentations and do not provide thorough descriptions of the material alone; for reference, read the corresponding sections from Algorithms, 4th edition. An effective strategy is to skim the textbook before the lecture, read it thoroughly soon afterwards, and complete the corresponding PrairieLearn quiz.

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