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
FAQs
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Creators
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.
Pricing
| Purchase Course | |
|---|---|
| Access to course materials | Available |
| Access to graded materials | Available |
| Receive a final grade | Available |
| Earn a shareable Course Certificate | Available |
Ratings and Reviews
NICE
Harder than the first two courses and I really enjoy it!
Another great course from Coursera!
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Excellent course, I found this course hard as compared to earlier two courses. Many of the Lectures needs to be viewed twice to understand to my minimum level of satisfaction. Quizzes make sure that you understand concepts well and programming assignments are excellent!