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).
Offered By
Algorithms SpecializationStanford UniversityAbout this Course
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Learner Career Outcomes
30%
started a new career after completing these courses
32%
got a tangible career benefit from this course
20%
got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 1 of 4 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 17 hours to complete
English
Subtitles: Arabic, French, Portuguese (Brazilian), Italian, Vietnamese, Korean, German, Russian, Turkish, English, Spanish, Chinese
Skills you will gain
AlgorithmsRandomized AlgorithmSorting AlgorithmDivide And Conquer Algorithms
Learner Career Outcomes
30%
started a new career after completing these courses
32%
got a tangible career benefit from this course
20%
got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 1 of 4 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 17 hours to complete
English
Subtitles: Arabic, French, Portuguese (Brazilian), Italian, Vietnamese, Korean, German, Russian, Turkish, English, Spanish, Chinese
Offered by
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.
Syllabus - What you will learn from this course
4 hours to complete
Week 1
Introduction; "big-oh" notation and asymptotic analysis.
4 hours to complete
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 #130m
Programming Assignment #130m
4 hours to complete
Week 2
Divide-and-conquer basics; the master method for analyzing divide and conquer algorithms.
4 hours to complete
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 #230m
Programming Assignment #230m
4 hours to complete
Week 3
The QuickSort algorithm and its analysis; probability review.
4 hours to complete
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 #330m
Programming Assignment #330m
5 hours to complete
Week 4
5 hours to complete
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 #430m
Programming Assignment #430m
Final Exam30m
Reviews
TOP REVIEWS FROM DIVIDE AND CONQUER, SORTING AND SEARCHING, AND RANDOMIZED ALGORITHMS
by KSSep 13, 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 DTMay 26, 2020
Thank you for teaching me this course. I learned a lot of new things, including Divide-and-Conquer, MergeSort, QuickSort, and Randomization Algorithms, along with proof for their asymptotic runtime
by FRMar 15, 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
by CVJun 10, 2017
A really exciting and challenging course. Loved the way the instructor explained everything with so much detail and precision. Definitely looking forward to the next course in the specialization.
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.
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