About this course: The primary topics in this part of the specialization are: greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes) and dynamic programming (knapsack, sequence alignment, optimal search trees).
Who is this class for: Learners with at least a little bit of programming experience who want to learn the essentials of algorithms. In a University computer science curriculum, this course is typically taken in the third year.
Created by: Stanford University
Taught by: Tim Roughgarden, Professor
Computer Science
| Basic Info | Course 3 of 4 in the Algorithms Specialization |
| Level | Intermediate |
| Commitment | 4 weeks of study, 4-8 hours/week |
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
Syllabus
WEEK 1
Week 1
Two motivating applications; selected review; introduction to greedy algorithms; a scheduling application; Prim's MST algorithm.
16 videos, 4 readings
- Reading: Week 1 Overview
- Reading: Overview, Resources, and Policies
- Reading: Lecture slides
- Video: Application: Sequence Alignment
- Video: Introduction to Greedy Algorithms
- Video: Application: Optimal Caching
- Video: Problem Definition
- Video: A Greedy Algorithm
- Video: Correctness Proof - Part I
- Video: Correctness Proof - Part II
- Video: Handling Ties [Advanced - Optional]
- Video: MST Problem Definition
- Video: Prim's MST Algorithm
- Video: Correctness Proof I
- Video: Correctness Proof II
- Video: Proof of Cut Property [Advanced - Optional]
- Video: Fast Implementation I
- Video: Fast Implementation II
- Reading: Optional Theory Problems (Week 1)
Graded: Problem Set #1
Graded: Programming Assignment #1
WEEK 2
Week 2
Kruskal's MST algorithm and applications to clustering; advanced union-find (optional).
16 videos, 2 readings
- Reading: Week 2 Overview
- Video: Correctness of Kruskal's Algorithm
- Video: Implementing Kruskal's Algorithm via Union-Find I
- Video: Implementing Kruskal's Algorithm via Union-Find II
- Video: MSTs: State-of-the-Art and Open Questions [Advanced - Optional]
- Video: Application to Clustering
- Video: Correctness of Clustering Algorithm
- Video: Lazy Unions [Advanced - Optional]
- Video: Union-by-Rank [Advanced - Optional]
- Video: Analysis of Union-by-Rank [Advanced - Optional]
- Video: Path Compression [Advanced - Optional]
- Video: Path Compression: The Hopcroft-Ullman Analysis I [Advanced - Optional]
- Video: Path Compression: The Hopcroft-Ullman Analysis II [Advanced - Optional]
- Video: The Ackermann Function [Advanced - Optional]
- Video: Path Compression: Tarjan's Analysis I [Advanced - Optional]
- Video: Path Compression: Tarjan's Analysis II [Advanced - Optional]
- Reading: Optional Theory Problems (Week 2)
Graded: Problem Set #2
Graded: Programming Assignment #2
WEEK 3
Week 3
Huffman codes; introduction to dynamic programming.
11 videos, 1 reading
- Reading: Week 3 Overview
- Video: Problem Definition
- Video: A Greedy Algorithm
- Video: A More Complex Example
- Video: Correctness Proof I
- Video: Correctness Proof II
- Video: Introduction: Weighted Independent Sets in Path Graphs
- Video: WIS in Path Graphs: Optimal Substructure
- Video: WIS in Path Graphs: A Linear-Time Algorithm
- Video: WIS in Path Graphs: A Reconstruction Algorithm
- Video: Principles of Dynamic Programming
Graded: Problem Set #3
Graded: Programming Assignment #3
WEEK 4
Week 4
Advanced dynamic programming: the knapsack problem, sequence alignment, and optimal binary search trees.
10 videos, 3 readings
- Reading: Week 4 Overview
- Video: A Dynamic Programming Algorithm
- Video: Example [Review - Optional]
- Video: Optimal Substructure
- Video: A Dynamic Programming Algorithm
- Video: Problem Definition
- Video: Optimal Substructure
- Video: Proof of Optimal Substructure
- Video: A Dynamic Programming Algorithm I
- Video: A Dynamic Programming Algorithm II
- Reading: Optional Theory Problems (Week 4)
- Reading: Info and FAQ for final exam
Graded: Problem Set #4
Graded: Programming Assignment #4
Graded: Final Exam
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Stanford University
The Leland Stanford Junior University, commonly referred to as Stanford University or Stanford, is an American private research university located in Stanford, California on an 8,180-acre (3,310 ha) campus near Palo Alto, California, United States.
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| Access to course materials | Available |
| Access to graded materials | Available |
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