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    • Data Structures And Algorithms

    필터링 기준

    "data structures and algorithms"에 대한 225개의 결과

    • University of California San Diego

      University of California San Diego

      Data Structures and Algorithms

      획득할 기술: Algorithms, Arrays, Business Analysis, C Programming Language Family, Computer Programming, Critical Thinking, Data Management, Data Structures, Graph Theory, Graphs, Mathematical Theory & Analysis, Mathematics, Operations Research, Python Programming, Research and Design, Statistical Programming, Strategy and Operations, Theoretical Computer Science

      4.6

      (15.1k개의 검토)

      Intermediate · Specialization

    • 무료

      Princeton University

      Princeton University

      Algorithms, Part I

      획득할 기술: Computer Programming, Algorithms, Data Management, Theoretical Computer Science, Data Structures, Sorting

      4.9

      (9.6k개의 검토)

      Intermediate · Course

    • Stanford University

      Stanford University

      Algorithms

      획득할 기술: Algorithms, Computer Programming, Data Management, Data Structures, General Statistics, Graph Theory, Graphs, Machine Learning, Mathematics, Operations Research, Probability & Statistics, Programming Principles, Research and Design, Sorting, Strategy and Operations, Theoretical Computer Science

      4.8

      (5.4k개의 검토)

      Intermediate · Specialization

    • 무료

      Princeton University

      Princeton University

      Algorithms, Part II

      획득할 기술: Data Structures, Algorithms, Theoretical Computer Science, Data Management, Sorting

      4.9

      (1.7k개의 검토)

      Intermediate · Course

    • University of California San Diego

      University of California San Diego

      Data Structures

      획득할 기술: Algorithms, Data Management, Computer Programming, Data Structures, C Programming Language Family, Data Type, Theoretical Computer Science

      4.6

      (4.8k개의 검토)

      Intermediate · Course

    • University of Colorado Boulder

      University of Colorado Boulder

      Data Science Foundations: Data Structures and Algorithms

      획득할 기술: Algorithms, Computational Logic, Computer Programming, Data Management, Data Structures, Entrepreneurship, Graph Theory, Leadership and Management, Mathematical Theory & Analysis, Mathematics, Operating Systems, Operations Research, Other Programming Languages, Programming Principles, Research and Design, Strategy and Operations, System Programming, Theoretical Computer Science

      4.6

      (176개의 검토)

      Advanced · Specialization

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      Tsinghua University

      Tsinghua University

      Data Structures and Algorithms

      획득할 기술: Algorithms, Data Management, Data Structures, Theoretical Computer Science

      2.5

      (32개의 검토)

      Intermediate · Specialization

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      University of Michigan

      University of Michigan

      Python for Everybody

      획득할 기술: Application Programming Interfaces, Computational Logic, Computer Networking, Computer Programming, Computer Programming Tools, Data Management, Data Structures, Database Administration, Database Application, Databases, Extract, Transform, Load, Javascript, Mathematical Theory & Analysis, Mathematics, Natural Language Processing, Programming Principles, Python Programming, SQL, Software Architecture, Software Engineering, Statistical Programming, Syntax, Theoretical Computer Science, Web, Web Development

      4.8

      (249.8k개의 검토)

      Beginner · Specialization

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      Google

      Google

      Google Data Analytics

      획득할 기술: Algorithms, Analysis, Application Development, Big Data, Budget Management, Business Analysis, Business Communication, Change Management, Cloud Computing, Communication, Computational Logic, Computer Networking, Computer Programming, Computer Programming Tools, Cryptography, Data Analysis, Data Analysis Software, Data Management, Data Mining, Data Model, Data Structures, Data Visualization, Data Visualization Software, Database Administration, Database Design, Databases, Decision Making, Design and Product, Econometrics, Entrepreneurship, Experiment, Extract, Transform, Load, Feature Engineering, Finance, General Statistics, Leadership and Management, Machine Learning, Mathematical Theory & Analysis, Mathematics, Network Security, Other Programming Languages, Plot (Graphics), Presentation, Probability & Statistics, Problem Solving, Product Design, Programming Principles, Project Management, R Programming, Research and Design, SQL, Security Engineering, Security Strategy, Small Data, Software, Software Engineering, Software Security, Spreadsheet Software, Statistical Analysis, Statistical Programming, Statistical Visualization, Storytelling, Strategy and Operations, Theoretical Computer Science

      4.8

      (63k개의 검토)

      Beginner · Professional Certificate

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      University of California San Diego

      University of California San Diego

      Object Oriented Java Programming: Data Structures and Beyond

      획득할 기술: Algorithms, Business Psychology, Communication, Computer Architecture, Computer Programming, Data Management, Data Structures, Entrepreneurship, Estimation, Graph Theory, Graphs, Hardware Design, Human Resources, Interview, Java (Software Platform), Java Programming, Javascript, Leadership and Management, Mathematics, Mobile Development, Probability & Statistics, Problem Solving, Programming Principles, Project Management, Statistical Tests, Strategy and Operations, Supply Chain and Logistics, Theoretical Computer Science, Web Development

      4.7

      (6.8k개의 검토)

      Intermediate · Specialization

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      무료

      Princeton University

      Princeton University

      Computer Science: Algorithms, Theory, and Machines

      획득할 기술: Algorithms, Programming Principles, Computer Programming, Java Programming, Computer Architecture, Data Structures, Mathematics, Mathematical Theory & Analysis, Theoretical Computer Science, Network Architecture, Mobile Development, Computational Logic, Human Computer Interaction, Computational Thinking, Data Management, Computer Networking, Computer Programming Tools

      4.8

      (343개의 검토)

      Intermediate · Course

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      Rice University

      Rice University

      Fundamentals of Computing

      획득할 기술: Algorithms, Applied Mathematics, Communication, Computer Programming, Data Management, Data Structures, Databases, Entrepreneurship, General Statistics, Graph Theory, Leadership and Management, Mathematics, Operations Research, Patient, Probability & Statistics, Problem Solving, Python Programming, Research and Design, SQL, Software Engineering, Statistical Programming, Theoretical Computer Science

      4.8

      (3.8k개의 검토)

      Beginner · Specialization

    data structures and algorithms과(와) 관련된 검색

    data structures and algorithms in python
    data structures and algorithms in java
    data structures and algorithms in c++
    data structures and algorithms specialization
    data structures and algorithms (i)
    data structures and algorithms (ii)
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    data structures and algorithms (iii)
    1234…19

    요약하자면, 여기에 가장 인기 있는 data structures and algorithms 강좌 10개가 있습니다.

    • Data Structures and Algorithms: University of California San Diego
    • Algorithms, Part I: Princeton University
    • Algorithms: Stanford University
    • Algorithms, Part II: Princeton University
    • Data Structures: University of California San Diego
    • Data Science Foundations: Data Structures and Algorithms: University of Colorado Boulder
    • Data Structures and Algorithms: Tsinghua University
    • Python for Everybody: University of Michigan
    • Google Data Analytics: Google
    • Object Oriented Java Programming: Data Structures and Beyond: University of California San Diego

    Algorithms에서 학습할 수 있는 스킬

    그래프 (22)
    수학적 최적화 (21)
    컴퓨터 프로그램 (20)
    데이터 구조 (19)
    문제 해결 (19)
    대수학 (12)
    컴퓨터 비전 (10)
    이산 수학 (10)
    그래프 이론 (10)
    이미지 처리 (10)
    선형 대수 (10)
    강화 학습 (10)

    Data Structures And Algorithms에 대한 자주 묻는 질문

    • Data Structures and Algorithms work together to solve computational problems, usually by enabling an algorithm to manipulate data efficiently. The algorithm uses a set of rules (the data) to find the greatest common divisor, with one example being YouTube tracking a user’s activities to display videos relevant to them. Actions such as “liking” or “disliking” a video create data structures that inform the direction of the algorithm, bringing content to users that they are more likely to find engaging.

      In the field of Marketing, Data Structures and Algorithms are commonly used to help organizations determine how to attract an audience to their online content—but they’re also used in the field of healthcare in Medical Algorithms. These are important to learn in order to calculate someone’s BMI, drug dosages, and more.‎

    • Data Structures and Algorithms go together like the tech industry and career opportunities—as long as people are using computers, they’ll both be in abundance. When concepts like running times, binary searches, dynamic programming, and others are nailed down, learners can begin to explore the wide variety of roles available to them. These roles include Platform Engineer, Graphics Engineer, Full-Stack Engineer, Backend Engineer, Product Analyst, Data Scientist, Data Engineer, Big Data Engineer, Data Architect, Application Developer, Mobile Developer, and others that are related.

      A search of “Data Structures and Algorithms” on LinkedIn’s job portal shows roughly 11,500 results in the U.S. alone, with opportunities at large and small tech firms.‎

    • Data Structures and Algorithms courses offered through Coursera equip learners with knowledge in common data structures that are used in various computational problems; typical use cases for certain data structures; principles and methods in the design and implementation of various data structures; and more.

      Lessons on Data Structures and Algorithms are taught by instructors from major universities, including University of California at San Diego and Tsinghua University. Learners can enjoy exploring Data Structures and Algorithms with instructors specializing in Computer Science, Technology, Mathematics, and other disciplines. Course content on Data Structures and Algorithms is delivered via video lectures, hands-on projects, readings, quizzes, and other types of assignments.‎

    • Some of the skills or experience you may need to have before learning data structures and algorithms include coding, some programming concepts, and a basic understanding of Java and Object-Oriented Programming (OOP). If you understand the concept of sorting algorithms, you may already have some skills needed to study the subject. Also, if you have an understanding of basic data structures such as linked lists, queues, matrices, stacks, and trees, you may have some solid skills needed to learn data structures and algorithms.‎

    • The kind of people who are best suited for roles in data structures and algorithms are focused on becoming programmers or software engineers/developers who have an emphasis on applications and scientific performance analysis. They are comfortable thinking outside the box for innovative ways to save a company money by using algorithms to solve problems. These professionals enjoy learning about giving computers the right sets of instructions so that they can skillfully solve very complex problems. They may also enjoy working in roles related to data structures and algorithms because they are energized by wanting to make software run properly and efficiently.‎

    • Learning data structures and algorithms may be right for you if you would like to advance your engineering or data science career. If you would like to learn how to apply basic algorithmic techniques, such as greedy algorithms, binary search, sorting, and dynamic programming to solve programming challenges, then studying the subject may be right for you. Learning data structures and algorithms might benefit you if you’d like to understand how to apply various data structures such as a stack, queue, hash table, priority queue, binary search tree, graph, and string to solve programming challenges, as well. But to understand how to reach a good algorithm, you’ll need to understand how to create a set of good data structures. Studying data sets and algorithms can benefit you if you need to learn how data structures are implemented in different programming languages.‎

    이 FAQ 콘텐츠는 정보 전달 목적만으로 사용할 수 있습니다. 학습자는 과정 및 기타 학점 정보가 개인적, 직업적 및 재정적 목표에 부합하는지 확인하기 위해 추가 조사를 수행하는 것이 좋습니다.
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