About this course: The primary topics in this part of the specialization are: shortest paths (Bellman-Ford, Floyd-Warshall, Johnson), NP-completeness and what it means for the algorithm designer, and strategies for coping with computationally intractable problems (analysis of heuristics, local search).
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 4 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
The Bellman-Ford algorithm; all-pairs shortest paths.
14 videos, 4 readings
- Reading: Week 1 Overview
- Reading: Overview, Resources, and Policies
- Reading: Lecture Slides
- Video: Single-Source Shortest Paths, Revisted
- Video: Optimal Substructure
- Video: The Basic Algorithm I
- Video: The Basic Algorithm II
- Video: Detecting Negative Cycles
- Video: A Space Optimization
- Video: Internet Routing I [Optional]
- Video: Internet Routing II [Optional]
- Video: Problem Definition
- Video: Optimal Substructure
- Video: The Floyd-Warshall Algorithm
- Video: A Reweighting Technique
- Video: Johnson's Algorithm I
- Video: Johnson's Algorithm II
- Reading: Optional Theory Problems (Week 1)
Graded: Problem Set #1
Graded: Programming Assignment #1
WEEK 2
Week 2
NP-complete problems and exact algorithms for them.
11 videos, 2 readings
- Reading: Week 2 Overview
- Video: Polynomial-Time Solvable Problems
- Video: Reductions and Completeness
- Video: Definition and Interpretation of NP-Completeness I
- Video: Definition and Interpretation of NP-Completeness II
- Video: The P vs. NP Question
- Video: Algorithmic Approaches to NP-Complete Problems
- Video: The Vertex Cover Problem
- Video: Smarter Search for Vertex Cover I
- Video: Smarter Search for Vertex Cover II
- Video: The Traveling Salesman Problem
- Video: A Dynamic Programming Algorithm for TSP
- Reading: Optional Theory Problems (Week 2)
Graded: Problem Set #2
Graded: Programming Assignment #2
WEEK 3
Week 3
Approximation algorithms for NP-complete problems.
6 videos, 1 reading
- Reading: Week 3 Overview
- Video: A Greedy Knapsack Heuristic
- Video: Analysis of a Greedy Knapsack Heuristic I
- Video: Analysis of a Greedy Knapsack Heuristic II
- Video: A Dynamic Programming Heuristic for Knapsack
- Video: Knapsack via Dynamic Programming, Revisited
- Video: Ananysis of Dynamic Programming Heuristic
Graded: Problem Set #3
Graded: Programming Assignment #3
WEEK 4
Week 4
Local search algorithms for NP-complete problems; the wider world of algorithms.
11 videos, 3 readings
- Reading: Week 4 Overview
- Video: The Maximum Cut Problem I
- Video: The Maximum Cut Problem II
- Video: Principles of Local Search I
- Video: Principles of Local Search II
- Video: The 2-SAT Problem
- Video: Random Walks on a Line
- Video: Analysis of Papadimitriou's Algorithm
- Video: Stable Matching [Optional]
- Video: Matchings, Flows, and Braess's Paradox [Optional]
- Video: Linear Programming and Beyond [Optional]
- Video: Epilogue
- 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
| Audit | Purchase Course | |
|---|---|---|
| Access to course materials | Available | Available |
| Access to graded materials | Not available | Available |
| Receive a final grade | Not available | Available |
| Earn a shareable Course Certificate | Not available | Available |
Ratings and Reviews
I really love this course. What the professor said was just to the points he wanted to convey and no not-related sentences. He controlled extremely well about to what level of details to unfold. Last but not least, he adds complexity of problems gradually. I saw he taught a follow-up course at Stanford and I can watch the videos on Youtube. If the course were on Coursera, I would take it.
Awesone Course!!!!
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SJ
This is the most challenging course of all the courses in the specialization