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
How It Works
Coursework
Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.
Help from Your Peers
Connect with thousands of other learners and debate ideas, discuss course material, and get help mastering concepts.
Certificates
Earn official recognition for your work, and share your success with friends, colleagues, and employers.
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
The lectures gives much more information than previous 3-courses. And I often found I need extra practices (on-line alg interview problems) and reading (CLRS, e.g.) to grasp the course materials. The programming assignments are also more demanding. However, after finishing this course, I believe I have achieved better and deeper understanding of Algorithm design and analysis than I could imaged before taking this final NP course. And I am looking forward to learn more from Professor Tim Roughguarden's 'a second course on Algorithm' on youtube. Thank you very much, professor! Your knowledge and passion is totally incredible! And Thank you very much for fellow students on the discussion forums. It has been a great pleasure to learn with you all :)
A great course with great assignments. Assignments really test your implementation skills as well as research skills. One should really use forums to ask doubts and give answers to solve these assignments.
Very challenging, but it just shows that you should never give up and keep believing in yourself! Thanks Prof. Tim for this excellent course. I do feel smarter than when I started, and had fun too (most of the time)!
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TN
Thanks for the instructor.