The course covers basic algorithmic techniques and ideas for computational problems arising frequently in practical applications: sorting and searching, divide and conquer, greedy algorithms, dynamic programming. We will learn a lot of theory: how to sort data and how it helps for searching; how to break a large problem into pieces and solve them recursively; when it makes sense to proceed greedily; how dynamic programming is used in genomic studies. You will practice solving computational problems, designing new algorithms, and implementing solutions efficiently (so that they run in less than a second).
Este curso forma parte de Programa Especializado - Estructuras de datos y algoritmos
Algorithmic Toolbox
ofrecido por
Universidad de California en San Diego
National Research University Higher School of Economics
Acerca de este Curso
4.7
4,100 calificaciones
Qué aprenderás
Essential algorithmic techniques
Design efficient algorithms
Practice solving algorithmic interview problems
Implement efficient and reliable solutions
Habilidades que obtendrás
Dynamic ProgrammingDebuggingSoftware TestingAlgorithmsComputer Programming
Programa - Qué aprenderás en este curso
Semana
1Programming Challenges
Welcome to the first module of Data Structures and Algorithms! Here we will provide an overview of where algorithms and data structures are used (hint: everywhere) and walk you through a few sample programming challenges. The programming challenges represent an important (and often the most difficult!) part of this specialization because the only way to fully understand an algorithm is to implement it. Writing correct and efficient programs is hard; please don’t be surprised if they don’t work as you planned—our first programs did not work either! We will help you on your journey through the specialization by showing how to implement your first programming challenges. We will also introduce testing techniques that will help increase your chances of passing assignments on your first attempt. In case your program does not work as intended, we will show how to fix it, even if you don’t yet know which test your implementation is failing on.
6 videos (Total 48 minutos), 5 readings, 3 quizzes
6 videos
Welcome!3m
Solving the Sum of Two Digits Programming Challenge (screencast)6m
Solving the Maximum Pairwise Product Programming Challenge: Improving the Naive Solution, Testing, Debugging13m
Stress Test - Implementation8m
Stress Test - Find the Test and Debug7m
Stress Test - More Testing, Submit and Pass!8m
5 lecturas
Companion MOOCBook10m
What background knowledge is necessary?10m
Optional Videos and Screencasts10m
Maximum Pairwise Product Programming Challenge10m
Acknowledgements2m
1 ejercicios de práctica
Solving Programming Challenges20m
Semana
2Algorithmic Warm-up
In this module you will learn that programs based on efficient algorithms can solve the same problem billions of times faster than programs based on naïve algorithms. You will learn how to estimate the running time and memory of an algorithm without even implementing it. Armed with this knowledge, you will be able to compare various algorithms, select the most efficient ones, and finally implement them as our programming challenges!
12 videos (Total 77 minutos), 3 readings, 4 quizzes
12 videos
Coming Up3m
Problem Overview3m
Naive Algorithm5m
Efficient Algorithm3m
Problem Overview and Naive Algorithm4m
Efficient Algorithm5m
Computing Runtimes10m
Asymptotic Notation6m
Big-O Notation6m
Using Big-O10m
Course Overview10m
3 lecturas
Resources2m
Resources2m
Resources2m
3 ejercicios de práctica
Logarithms10m
Big-O10m
Growth rate10m
Semana
3Greedy Algorithms
In this module you will learn about seemingly naïve yet powerful class of algorithms called greedy algorithms. After you will learn the key idea behind the greedy algorithms, you may feel that they represent the algorithmic Swiss army knife that can be applied to solve nearly all programming challenges in this course. But be warned: with a few exceptions that we will cover, this intuitive idea rarely works in practice! For this reason, it is important to prove that a greedy algorithm always produces an optimal solution before using this algorithm. In the end of this module, we will test your intuition and taste for greedy algorithms by offering several programming challenges.
10 videos (Total 56 minutos), 1 reading, 3 quizzes
10 videos
Car Fueling7m
Car Fueling - Implementation and Analysis9m
Main Ingredients of Greedy Algorithms2m
Celebration Party Problem6m
Efficient Algorithm for Grouping Children5m
Analysis and Implementation of the Efficient Algorithm5m
Long Hike6m
Fractional Knapsack - Implementation, Analysis and Optimization6m
Review of Greedy Algorithms2m
1 lecturas
Resources2m
2 ejercicios de práctica
Greedy Algorithms10m
Fractional Knapsack10m
Semana
4Divide-and-Conquer
In this module you will learn about a powerful algorithmic technique called Divide and Conquer. Based on this technique, you will see how to search huge databases millions of times faster than using naïve linear search. You will even learn that the standard way to multiply numbers (that you learned in the grade school) is far from the being the fastest! We will then apply the divide-and-conquer technique to design two efficient algorithms (merge sort and quick sort) for sorting huge lists, a problem that finds many applications in practice. Finally, we will show that these two algorithms are optimal, that is, no algorithm can sort faster!
20 videos (Total 157 minutos), 5 readings, 6 quizzes
20 videos
Intro3m
Linear Search7m
Binary Search7m
Binary Search Runtime8m
Problem Overview and Naïve Solution6m
Naïve Divide and Conquer Algorithm7m
Faster Divide and Conquer Algorithm6m
What is the Master Theorem?4m
Proof of the Master Theorem9m
Problem Overview2m
Selection Sort8m
Merge Sort10m
Lower Bound for Comparison Based Sorting12m
Non-Comparison Based Sorting Algorithms7m
Overview2m
Algorithm9m
Random Pivot13m
Running Time Analysis (optional)15m
Equal Elements6m
Final Remarks8m
5 lecturas
Resources10m
Resources5m
Resources10m
Resources5m
Resources10m
5 ejercicios de práctica
Linear Search and Binary Search10m
Polynomial Multiplication15m
Master Theorem10m
Sorting15m
Quick Sort15m
38%
comenzó una nueva carrera después de completar estos cursos
38%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
14%
consiguió un aumento de sueldo o ascenso
Principales revisiones
por SG•Jan 20th 2017
I liked the fact that the algorithms are not just the introductory searching and sorting algorithms. The assignments are fairly difficult (I have decent scripting experience), but not impossibly so.
por MB•Mar 6th 2018
Cool course. Thank you! One suggestion about your book (Learning Algorithms Through Programming and Puzzle Solving): could you add some theory which would serve as a brief reminder before problems?
Instructores
Alexander S. Kulikov
Visiting ProfessorDepartment of Computer Science and Engineering
Michael Levin
LecturerComputer Science
Neil Rhodes
Adjunct FacultyComputer Science and Engineering
Pavel Pevzner
ProfessorDepartment of Computer Science and Engineering
Daniel M Kane
Assistant ProfessorDepartment of Computer Science and Engineering / Department of Mathematics
Acerca de Universidad de California en San Diego
UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory.
Acerca de National Research University Higher School of Economics
National Research University - Higher School of Economics (HSE) is one of the top research universities in Russia. Established in 1992 to promote new research and teaching in economics and related disciplines, it now offers programs at all levels of university education across an extraordinary range of fields of study including business, sociology, cultural studies, philosophy, political science, international relations, law, Asian studies, media and communicamathematics, engineering, and more.
Learn more on www.hse.ru
Acerca del programa especializado Estructuras de datos y algoritmos
This specialization is a mix of theory and practice: you will learn algorithmic techniques for solving various computational problems and will implement about 100 algorithmic coding problems in a programming language of your choice. No other online course in Algorithms even comes close to offering you a wealth of programming challenges that you may face at your next job interview. To prepare you, we invested over 3000 hours into designing our challenges as an alternative to multiple choice questions that you usually find in MOOCs. Sorry, we do not believe in multiple choice questions when it comes to learning algorithms...or anything else in computer science! For each algorithm you develop and implement, we designed multiple tests to check its correctness and running time — you will have to debug your programs without even knowing what these tests are! It may sound difficult, but we believe it is the only way to truly understand how the algorithms work and to master the art of programming. The specialization contains two real-world projects: Big Networks and Genome Assembly. You will analyze both road networks and social networks and will learn how to compute the shortest route between New York and San Francisco (1000 times faster than the standard shortest path algorithms!) Afterwards, you will learn how to assemble genomes from millions of short fragments of DNA and how assembly algorithms fuel recent developments in personalized medicine.
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.
¿Qué recibiré si me suscribo a este Programa especializado?
Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.
¿Cuál es la política de reembolsos?
¿Hay ayuda económica disponible?
¿Tienes más preguntas? Visita el Centro de Ayuda al Alumno.
Coursera brinda acceso universal a la mejor educación del mundo, al asociarse con las mejores universidades y organizaciones, para ofrecer cursos en línea.
© 2019 Coursera Inc. Todos los derechos reservados.
