This course covers basics of algorithm design and analysis, as well as algorithms for sorting arrays, data structures such as priority queues, hash functions, and applications such as Bloom filters.
このコースはData Science Foundations: Data Structures and Algorithms専門講座に属します。
11,919人がすでに登録済みです
Data Science Foundations: Data Structures and Algorithms専門講座コロラド大学ボルダー校（University of Colorado Boulder）このコースについて
63,430 最近の表示
柔軟性のある期限
スケジュールに従って期限をリセットします。
共有できる証明書
修了時に証明書を取得
100%オンライン
自分のスケジュールですぐに学習を始めてください。
中級レベル
Calculus: derivatives and integrals. Probability theory: distributions, expectations, and moments. Some programming experience with Python.
約35時間で修了
英語
字幕：英語
学習内容
Explain fundamental concepts for algorithmic searching and sorting
Describe heap data structures and analyze heap components, such as arrays and priority queues
Design basic algorithms to implement sorting, selection, and hash functions in heap data structures
習得するスキル
- Analysis of Algorithms
- Hashtables
- Algorithm Design
- Python Programming
- Data Structure Design
柔軟性のある期限
スケジュールに従って期限をリセットします。
共有できる証明書
修了時に証明書を取得
100%オンライン
自分のスケジュールですぐに学習を始めてください。
中級レベル
Calculus: derivatives and integrals. Probability theory: distributions, expectations, and moments. Some programming experience with Python.
約35時間で修了
英語
字幕：英語
提供：
コロラド大学ボルダー校（University of Colorado Boulder）
CU-Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies.
修士号の取得を目指しましょう
この コース は コロラド大学ボルダー校（University of Colorado Boulder） の100%オンラインの Master of Science in Data Science の一部です。
プログラムのすべてで認定されれば、それらのコースが学位学習に加算されます。
シラバス - 本コースの学習内容
10時間で修了
Basics of Algorithms Through Searching and Sorting
In this module the student will learn the very basics of algorithms through three examples: insertion sort (sort an array in ascending/descending order); binary search: search whether an element is present in a sorted array and if yes, find its index; and merge sort (a faster method for sorting an array). Through these algorithms the student will be introduced to the analysis of algorithms -- i.e, proving that the algorithm is correct for the task it has been designed for and establishing a bound on how the time taken to execute the algorithm grows as a function of input. The student is also exposed to the notion of a faster algorithm and asymptotic complexity through the O, big-Omega and big-Theta notations.
10時間で修了
7件のビデオ （合計202分）, 10 学習用教材, 5 個のテスト
9時間で修了
Heaps and Hashtable Data Structures
In this module, the student will learn about the basics of data structures that organize data to make certain types of operations faster. The module starts with a broad introduction to data structures and talks about some simple data structures such as first-in first out queues and last-in first out stack. Next, we introduce the heap data structure and the basic properties of heaps. This is followed by algorithms for insertion, deletion and finding the minimum element of a heap along with their time complexities. Finally, we will study the priority queue data structure and showcase some applications.
9時間で修了
5件のビデオ （合計120分）, 6 学習用教材, 6 個のテスト
9時間で修了
Randomization: Quicksort, Quickselect, and Hashtables
We will go through the quicksort and quickselect algorithms for sorting and selecting the kth smallest element in an array efficiently. This will also be an introduction to the role of randomization in algorithm design. Next, we will study hashtables: a highly useful data structure that allows for efficient search and retrieval from large amounts of data. We will learn about the basic principles of hash-table and operations on hashtables.
9時間で修了
7件のビデオ （合計152分）, 6 学習用教材, 6 個のテスト
6時間で修了
Applications of Hashtables
In this module, we will learn randomized pivot selection for quicksort and quickselect. We will learn how to analyze the complexity of the randomized quicksort/quickselect algorithms. We will learn open address hashing: a technique that simplifies hashtable design. Next we will study the design of hash functions and their analysis. Finally, we present and analyze Bloom filters that are used in various applications such as querying streaming data and counting.
6時間で修了
5件のビデオ （合計113分）, 6 学習用教材, 2 個のテスト
レビュー
- 5 stars84.55%
- 4 stars8.82%
- 3 stars1.47%
- 2 stars1.47%
- 1 star3.67%
ALGORITHMS FOR SEARCHING, SORTING, AND INDEXING からの人気レビュー
SKにより2021年8月28日
Could gain valuable insights for my future computer science projects.
PGにより2021年8月10日
The lectures were very informative and I learned a lot
RMにより2022年4月24日
The lectures are delivered with just the right amount of math, intuition and examples.
WZにより2022年3月20日
The videos are super great! The professor explains everything clearly. However, the assignments are not that polished. There are tons of typos.
Data Science Foundations: Data Structures and Algorithms専門講座について
Building fast and highly performant data science applications requires an intimate knowledge of how data can be organized in a computer and how to efficiently perform operations such as sorting, searching, and indexing. This course will teach the fundamentals of data structures and algorithms with a focus on data science applications. This specialization is targeted towards learners who are broadly interested in programming applications that process large amounts of data (expertise in data science is not required), and are familiar with the basics of programming in python. We will learn about various data structures including arrays, hash-tables, heaps, trees and graphs along with algorithms including sorting, searching, traversal and shortest path algorithms.
よくある質問
いつ講座や課題にアクセスできるようになりますか？
この専門講座をサブスクライブすると何を行うことができるようになりますか？
学資援助はありますか？
さらに質問がある場合は、受講者ヘルプセンターにアクセスしてください。
