Este curso faz parte do Programa de cursos integrados Data Structures and Algorithms
Algorithmic Toolbox
oferecido por
University of California San Diego
National Research University Higher School of Economics
Informações sobre o curso
4.7
3,585 classificações
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).
Habilidades que você terá
AlgorithmsDynamic ProgrammingGreedy AlgorithmDivide And Conquer Algorithms
Programa - O que você aprenderá com este curso
1
Seção
Programming 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 vídeos (Total de 48 min), 4 leituras, 2 testes
6 videos
Welcome!3min
Solving the Sum of Two Digits Programming Challenges (screencast)6min
Solving the Maximum Pairwise Product Programming Challenge: Improving the Naive Solution, Testing, Debugging13min
Stress Test - Implementation8min
Stress Test - Find the Test and Debug7min
Stress Test - More Testing, Submit and Pass!8min
4 leituras
Companion MOOCBook10min
What background knowledge is necessary?10min
Optional Videos and Screencasts10min
Acknowledgements2min
1 exercício prático
Solving Programming Challenges20min
2
Seção
Algorithmic 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 vídeos (Total de 77 min), 3 leituras, 4 testes
12 videos
Coming Up3min
Problem Overview3min
Naive Algorithm5min
Efficient Algorithm3min
Problem Overview and Naive Algorithm4min
Efficient Algorithm5min
Computing Runtimes10min
Asymptotic Notation6min
Big-O Notation6min
Using Big-O10min
Course Overview10min
3 leituras
Resources2min
Resources2min
Resources2min
3 exercícios práticos
Logarithms10min
Big-O10min
Growth rate10min
3
Seção
Greedy 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 vídeos (Total de 56 min), 1 leitura, 3 testes
10 videos
Largest Number2min
Car Fueling7min
Car Fueling - Implementation and Analysis9min
Main Ingredients of Greedy Algorithms2min
Celebration Party Problem6min
Efficient Algorithm for Grouping Children5min
Analysis and Implementation of the Efficient Algorithm5min
Long Hike6min
Fractional Knapsack - Implementation, Analysis and Optimization6min
Review of Greedy Algorithms2min
1 leituras
Resources2min
2 exercícios práticos
Greedy Algorithms10min
Fractional Knapsack10min
4
Seção
Divide-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 vídeos (Total de 157 min), 5 leituras, 6 testes
20 videos
Intro3min
Linear Search7min
Binary Search7min
Binary Search Runtime8min
Problem Overview and Naïve Solution6min
Naïve Divide and Conquer Algorithm7min
Faster Divide and Conquer Algorithm6min
What is the Master Theorem?4min
Proof of the Master Theorem9min
Problem Overview2min
Selection Sort8min
Merge Sort10min
Lower Bound for Comparison Based Sorting12min
Non-Comparison Based Sorting Algorithms7min
Overview2min
Algorithm9min
Random Pivot13min
Running Time Analysis (optional)15min
Equal Elements6min
Final Remarks8min
5 leituras
Resources10min
Resources5min
Resources10min
Resources5min
Resources10min
5 exercícios práticos
Linear Search and Binary Search10min
Polynomial Multiplication15min
Master Theorem10min
Sorting15min
Quick Sort15min
4.7
29%
83%
11%
Melhores avaliações
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?
Instrutores
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
Sobre University of California 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.
Sobre 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 communications, IT, mathematics, engineering, and more.
Learn more on www.hse.ru
Sobre o Programa de cursos integrados Data Structures and Algorithms
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.
Perguntas Frequentes – FAQ
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?
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