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).
This course is part of the Algorithms Specialization
Divide and Conquer, Sorting and Searching, and Randomized Algorithms
Offered By
About this Course
4.8
2,362 ratings
Skills you will gain
AlgorithmsRandomized AlgorithmSorting AlgorithmDivide And Conquer Algorithms
Syllabus - What you will learn from this course
Week
13 hours to complete
Week 1
Introduction; "big-oh" notation and asymptotic analysis.
13 videos (Total 130 min), 3 readings, 2 quizzes
13 videos
Integer Multiplication8m
Karatsuba Multiplication12m
About the Course17m
Merge Sort: Motivation and Example8m
Merge Sort: Pseudocode12m
Merge Sort: Analysis9m
Guiding Principles for Analysis of Algorithms15m
The Gist14m
Big-Oh Notation4m
Basic Examples7m
Big Omega and Theta7m
Additional Examples [Review - Optional]7m
3 readings
Welcome and Week 1 Overview10m
Overview, Resources, and Policies10m
Lecture slides10m
2 practice exercises
Problem Set #110m
Programming Assignment #12m
Week
23 hours to complete
Week 2
Divide-and-conquer basics; the master method for analyzing divide and conquer algorithms.
11 videos (Total 170 min), 2 readings, 2 quizzes
11 videos
O(n log n) Algorithm for Counting Inversions II16m
Strassen's Subcubic Matrix Multiplication Algorithm22m
O(n log n) Algorithm for Closest Pair I [Advanced - Optional]31m
O(n log n) Algorithm for Closest Pair II [Advanced - Optional]18m
Motivation7m
Formal Statement10m
Examples13m
Proof I9m
Interpretation of the 3 Cases10m
Proof II16m
2 readings
Week 2 Overview10m
Optional Theory Problems (Batch #1)10m
2 practice exercises
Problem Set #210m
Programming Assignment #22m
Week
33 hours to complete
Week 3
The QuickSort algorithm and its analysis; probability review.
9 videos (Total 156 min), 1 reading, 2 quizzes
9 videos
Partitioning Around a Pivot24m
Correctness of Quicksort [Review - Optional]10m
Choosing a Good Pivot22m
Analysis I: A Decomposition Principle21m
Analysis II: The Key Insight11m
Analysis III: Final Calculations8m
Probability Review I25m
Probability Review II17m
1 reading
Week 3 Overview10m
2 practice exercises
Problem Set #310m
Programming Assignment #36m
Week
44 hours to complete
Week 4
Linear-time selection; graphs, cuts, and the contraction algorithm.
11 videos (Total 184 min), 3 readings, 3 quizzes
11 videos
Randomized Selection - Analysis20m
Deterministic Selection - Algorithm [Advanced - Optional]16m
Deterministic Selection - Analysis I [Advanced - Optional]22m
Deterministic Selection - Analysis II [Advanced - Optional]12m
Omega(n log n) Lower Bound for Comparison-Based Sorting [Advanced - Optional]13m
Graphs and Minimum Cuts15m
Graph Representations14m
Random Contraction Algorithm8m
Analysis of Contraction Algorithm30m
Counting Minimum Cuts7m
3 readings
Week 4 Overview10m
Optional Theory Problems (Batch #2)10m
Info and FAQ for final exam10m
3 practice exercises
Problem Set #410m
Programming Assignment #42m
Final Exam20m
4.8
449 Reviews32%
started a new career after completing these courses
36%
got a tangible career benefit from this course
29%
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Top Reviews
By KS•Sep 14th 2018
Well researched. Topics covered well, with walkthrough for exam.le cases for each new introduced algorithm. Great experience, learned a lot of important algorithms and algorithmic thinking practices.
By FR•Mar 16th 2017
Very good course in algorithms. I bought the book to help me understand but the lectures make it way easier and thus much more fun to understand the analysis. Looking forward to complete the spec
Instructor
Tim Roughgarden
ProfessorComputer Science
About 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.
About the Algorithms Specialization
Algorithms are the heart of computer science, and the subject has countless practical applications as well as intellectual depth. This specialization is an introduction to algorithms for learners with at least a little programming experience. The specialization is rigorous but emphasizes the big picture and conceptual understanding over low-level implementation and mathematical details. After completing this specialization, you will be well-positioned to ace your technical interviews and speak fluently about algorithms with other programmers and computer scientists.
About the instructor: Tim Roughgarden has been a professor in the Computer Science Department at Stanford University since 2004. He has taught and published extensively on the subject of algorithms and their applications.
Frequently Asked Questions
When will I have access to the lectures and assignments?
Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
Is financial aid available?
More questions? Visit the Learner Help Center.
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