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
About this Course
Skills you will gain
- Randomized Algorithm
- Sorting Algorithm
- Divide And Conquer Algorithms
Syllabus - What you will learn from this course
- 5 stars83.05%
- 4 stars13.66%
- 3 stars1.80%
- 2 stars0.57%
- 1 star0.89%
TOP REVIEWS FROM DIVIDE AND CONQUER, SORTING AND SEARCHING, AND RANDOMIZED ALGORITHMS
very intansive ,it has really challenged my knowledge level both in english language or in computational mathematics,i feel too configent now.thank Stanford University,thanks Coursera
Challenging and eye opening to algorithm design paradigms. As a code writer for data analysis in a scientific field, this course really motivated me to delve deeper in this rich field.
As someone with only (UK) high school level maths I just about managed to follow this. I am still confused by logarithms. I guess I should go and read the maths for computer science resource.
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.
About the Algorithms Specialization
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