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).
Este curso forma parte de Programa Especializado - Algoritmos
Divide and Conquer, Sorting and Searching, and Randomized Algorithms
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Acerca de este Curso
184,143 vistas recientes
Habilidades que obtendrás
AlgorithmsRandomized AlgorithmSorting AlgorithmDivide And Conquer Algorithms
Los estudiantes que toman este Course son
- Machine Learning Engineers
- Data Scientists
- Software Engineers
- Technical Leads
- Data Engineers
Programa - Qué aprenderás en este curso
Semana
13 horas para completar
Week 1
Introduction; "big-oh" notation and asymptotic analysis.
13 videos (Total 130 minutos), 3 lecturas, 2 cuestionarios
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 lecturas
Welcome and Week 1 Overview10m
Overview, Resources, and Policies10m
Lecture slides10m
2 ejercicios de práctica
Problem Set #110m
Programming Assignment #12m
Semana
23 horas para completar
Week 2
Divide-and-conquer basics; the master method for analyzing divide and conquer algorithms.
11 videos (Total 170 minutos), 2 lecturas, 2 cuestionarios
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 lecturas
Week 2 Overview10m
Optional Theory Problems (Batch #1)10m
2 ejercicios de práctica
Problem Set #210m
Programming Assignment #22m
Semana
33 horas para completar
Week 3
The QuickSort algorithm and its analysis; probability review.
9 videos (Total 156 minutos), 1 lectura, 2 cuestionarios
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 lecturas
Week 3 Overview10m
2 ejercicios de práctica
Problem Set #310m
Programming Assignment #36m
Semana
44 horas para completar
Week 4
Linear-time selection; graphs, cuts, and the contraction algorithm.
11 videos (Total 184 minutos), 3 lecturas, 3 cuestionarios
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 lecturas
Week 4 Overview10m
Optional Theory Problems (Batch #2)10m
Info and FAQ for final exam10m
3 ejercicios de práctica
Problem Set #410m
Programming Assignment #42m
Final Exam20m
36%
comenzó una nueva carrera después de completar estos cursos
37%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
27%
consiguió un aumento de sueldo o ascenso
Principales revisiones sobre Divide and Conquer, Sorting and Searching, and Randomized Algorithms
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.
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
Instructores
Tim Roughgarden
ProfessorComputer Science
Acerca de Universidad de Stanford
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.
Acerca de Programa especializado Algoritmos
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.
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