About this course: The primary topics in this part of the specialization are: asymptotic ("Big-oh") notation, sorting and searching, divide and conquer (master method, integer and matrix multiplication, closest pair), and randomized algorithms (QuickSort, contraction algorithm for min cuts).
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 1 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
Introduction; "big-oh" notation and asymptotic analysis.
13 videos, 3 readings
- Reading: Welcome and Week 1 Overview
- Reading: Overview, Resources, and Policies
- Reading: Lecture slides
- Video: Why Study Algorithms?
- Video: Integer Multiplication
- Video: Karatsuba Multiplication
- Video: About the Course
- Video: Merge Sort: Motivation and Example
- Video: Merge Sort: Pseudocode
- Video: Merge Sort: Analysis
- Video: Guiding Principles for Analysis of Algorithms
- Video: The Gist
- Video: Big-Oh Notation
- Video: Basic Examples
- Video: Big Omega and Theta
- Video: Additional Examples [Review - Optional]
Graded: Problem Set #1
Graded: Programming Assignment #1
WEEK 2
Week 2
Divide-and-conquer basics; the master method for analyzing divide and conquer algorithms.
11 videos, 2 readings
- Reading: Week 2 Overview
- Video: O(n log n) Algorithm for Counting Inversions I
- Video: O(n log n) Algorithm for Counting Inversions II
- Video: Strassen's Subcubic Matrix Multiplication Algorithm
- Video: O(n log n) Algorithm for Closest Pair I [Advanced - Optional]
- Video: O(n log n) Algorithm for Closest Pair II [Advanced - Optional]
- Video: Motivation
- Video: Formal Statement
- Video: Examples
- Video: Proof I
- Video: Interpretation of the 3 Cases
- Video: Proof II
- Reading: Optional Theory Problems (Batch #1)
Graded: Problem Set #2
Graded: Programming Assignment #2
WEEK 3
Week 3
The QuickSort algorithm and its analysis; probability review.
9 videos, 1 reading
- Reading: Week 3 Overview
- Video: Quicksort: Overview
- Video: Partitioning Around a Pivot
- Video: Correctness of Quicksort [Review - Optional]
- Video: Choosing a Good Pivot
- Video: Analysis I: A Decomposition Principle
- Video: Analysis II: The Key Insight
- Video: Analysis III: Final Calculations
- Video: Probability Review I
- Video: Probability Review II
Graded: Problem Set #3
Graded: Programming Assignment #3
WEEK 4
Week 4
Linear-time selection; graphs, cuts, and the contraction algorithm.
11 videos, 3 readings
- Reading: Week 4 Overview
- Video: Randomized Selection - Algorithm
- Video: Randomized Selection - Analysis
- Video: Deterministic Selection - Algorithm [Advanced - Optional]
- Video: Deterministic Selection - Analysis I [Advanced - Optional]
- Video: Deterministic Selection - Analysis II [Advanced - Optional]
- Video: Omega(n log n) Lower Bound for Comparison-Based Sorting [Advanced - Optional]
- Video: Graphs and Minimum Cuts
- Video: Graph Representations
- Video: Random Contraction Algorithm
- Video: Analysis of Contraction Algorithm
- Video: Counting Minimum Cuts
- Reading: Optional Theory Problems (Batch #2)
- 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
| 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
Now I truly understand how to think of algorithm in terms with Recursion applying Divide and Conquer, and how to use Master method to prove an algorithm's complexity. Even though it is more rigorous then what is required for a software interview or engineering project, having the exposure of theory is better than not having it.
Finished part I, keep going! This is one of the best courses in Coursera.
I loved the problem set 1!
Thanks for the book recommendations also
Coursera provides universal access to the world’s best education,
partnering with top universities and organizations to offer courses online.
© 2018 Coursera Inc. All rights reserved.
Great learning experience