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Results for "algorithms"

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    Stanford University

    Algorithms

    Skills you'll gain: Data Structures, Graph Theory, Algorithms, Bioinformatics, Theoretical Computer Science, Network Model, Programming Principles, Social Network Analysis, Network Analysis, Computational Thinking, Analysis, Computer Science, Network Routing, Probability, Pseudocode, Computational Logic, Operations Research

    4.8
    Rating, 4.8 out of 5 stars
    ·
    6K reviews

    Intermediate · Specialization · 3 - 6 Months

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    U

    University of California San Diego

    Data Structures and Algorithms

    Skills you'll gain: Data Structures, Graph Theory, Algorithms, Program Development, Bioinformatics, Data Storage, Development Testing, Theoretical Computer Science, Computational Thinking, Network Analysis, Test Case, Programming Principles, Computer Programming, Python Programming, C and C++, Java, Rust (Programming Language), Javascript, Software Testing, Debugging

    4.6
    Rating, 4.6 out of 5 stars
    ·
    17K reviews

    Intermediate · Specialization · 3 - 6 Months

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    Princeton University

    Algorithms, Part I

    Skills you'll gain: Data Structures, Algorithms, Java, Performance Testing, Computer Programming, Java Programming, Theoretical Computer Science, Object Oriented Programming (OOP)

    4.9
    Rating, 4.9 out of 5 stars
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    12K reviews

    Intermediate · Course · 3 - 6 Months

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    Microsoft

    Data Structures and Algorithms

    Skills you'll gain: Graph Theory, Data Structures, Microsoft Copilot, .NET Framework, Algorithms, Back-End Web Development, C# (Programming Language), Performance Tuning, Programming Principles, Server Side, Scalability, Application Performance Management

    4.8
    Rating, 4.8 out of 5 stars
    ·
    22 reviews

    Beginner · Course · 1 - 3 Months

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    IBM

    Python for Data Science, AI & Development

    Skills you'll gain: Data Import/Export, Programming Principles, Web Scraping, File I/O, Python Programming, Jupyter, Data Structures, Data Processing, Pandas (Python Package), Data Manipulation, JSON, Computer Programming, Restful API, NumPy, Object Oriented Programming (OOP), Scripting, Application Programming Interface (API), Automation, Data Analysis

    4.6
    Rating, 4.6 out of 5 stars
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    43K reviews

    Beginner · Course · 1 - 3 Months

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    Princeton University

    Algorithms, Part II

    Skills you'll gain: Graph Theory, Data Structures, Algorithms, Theoretical Computer Science, Operations Research, Computational Thinking, Computer Programming, Network Routing, Java Programming, Linear Algebra

    4.9
    Rating, 4.9 out of 5 stars
    ·
    2K reviews

    Intermediate · Course · 3 - 6 Months

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    University of Colorado Boulder

    Foundations of Data Structures and Algorithms

    Skills you'll gain: Theoretical Computer Science, Algorithms, Graph Theory, Data Structures, Operations Research, Public Key Cryptography Standards (PKCS), Cryptography, Programming Principles, Computational Thinking, Pseudocode, Design Strategies, Data Encryption Standard, Computer Science, Tree Maps, Encryption, Linear Algebra, Combinatorics, Mathematical Modeling, Advanced Mathematics, Python Programming

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    4.6
    Rating, 4.6 out of 5 stars
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    908 reviews

    Advanced · Specialization · 3 - 6 Months

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    Meta

    Coding Interview Preparation

    Skills you'll gain: Data Structures, Algorithms, Software Visualization, Pseudocode, Programming Principles, Computational Thinking, Theoretical Computer Science, Computer Science, Technical Communication, Communication

    4.6
    Rating, 4.6 out of 5 stars
    ·
    764 reviews

    Intermediate · Course · 1 - 4 Weeks

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    Princeton University

    Computer Science: Algorithms, Theory, and Machines

    Skills you'll gain: Theoretical Computer Science, Data Structures, Computer Science, Computer Architecture, Algorithms, Programming Principles, Computational Logic, Java Programming, Computer Hardware, Scalability

    4.7
    Rating, 4.7 out of 5 stars
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    740 reviews

    Intermediate · Course · 1 - 3 Months

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    Amazon

    Data Structures and Algorithms

    Skills you'll gain: JUnit, Test Driven Development (TDD), Version Control, Git (Version Control System), GitHub, Performance Tuning, Unit Testing, Data Structures, Java Programming, Algorithms, Software Testing, Java, Computer Programming, Software Development, Scalability

    4.2
    Rating, 4.2 out of 5 stars
    ·
    53 reviews

    Beginner · Course · 1 - 4 Weeks

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    Codio

    C++: Data Structures and Algorithms

    Skills you'll gain: Computational Thinking, Algorithms, Graph Theory, Data Structures, C++ (Programming Language), C and C++, Programming Principles, Computer Programming, Object Oriented Programming (OOP), Technical Design, Theoretical Computer Science

    4.5
    Rating, 4.5 out of 5 stars
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    15 reviews

    Intermediate · Specialization · 1 - 3 Months

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    Free
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    Princeton University

    Analysis of Algorithms

    Skills you'll gain: Combinatorics, Algorithms, Theoretical Computer Science, Mathematical Theory & Analysis, Graph Theory, Data Structures, Advanced Mathematics, Mathematical Modeling, Probability

    4.4
    Rating, 4.4 out of 5 stars
    ·
    1K reviews

    Advanced · Course · 1 - 3 Months

What brings you to Coursera today?

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In summary, here are 10 of our most popular algorithms courses

  • Algorithms: Stanford University
  • Data Structures and Algorithms: University of California San Diego
  • Algorithms, Part I: Princeton University
  • Data Structures and Algorithms: Microsoft
  • Python for Data Science, AI & Development: IBM
  • Algorithms, Part II: Princeton University
  • Foundations of Data Structures and Algorithms: University of Colorado Boulder
  • Coding Interview Preparation: Meta
  • Computer Science: Algorithms, Theory, and Machines: Princeton University
  • Data Structures and Algorithms: Amazon

Skills you can learn in Algorithms

Graphs (22)
Mathematical Optimization (21)
Computer Program (20)
Data Structure (19)
Problem Solving (19)
Algebra (12)
Computer Vision (10)
Discrete Mathematics (10)
Graph Theory (10)
Image Processing (10)
Linear Algebra (10)
Reinforcement Learning (10)

Frequently Asked Questions about Algorithms

A background in algorithms can lead to various career opportunities. Positions such as software developer, data scientist, systems analyst, and algorithm engineer are common paths. Additionally, roles in artificial intelligence and machine learning often require a strong understanding of algorithms. Companies across industries seek professionals who can design and implement effective algorithms to enhance their products and services.‎

To learn algorithms effectively, you should focus on several key skills. First, a solid understanding of programming languages such as Python, Java, or C++ is essential. Familiarity with data structures, such as arrays, linked lists, and trees, is also important, as they are often used in algorithm design. Problem-solving skills and analytical thinking will help you approach challenges creatively and efficiently.‎

There are many excellent online courses available for learning algorithms. For a comprehensive understanding, consider the Data Structures and Algorithms Specialization or the Algorithms Specialization. These programs cover foundational concepts and practical applications, making them suitable for learners at various levels.‎

Yes. You can start learning algorithms on Coursera for free in two ways:

  1. Preview the first module of many algorithms courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

If you want to keep learning, earn a certificate in algorithms, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

To learn algorithms, start by selecting a course that matches your current skill level. Engage with the course materials, complete exercises, and practice coding challenges. Utilize online resources, such as coding platforms, to reinforce your learning. Collaborating with peers or joining study groups can also enhance your understanding and provide support.‎

Typical topics covered in algorithms courses include sorting and searching algorithms, graph algorithms, dynamic programming, and algorithm complexity analysis. Additionally, courses may explore advanced topics such as machine learning algorithms and optimization techniques, providing a well-rounded understanding of how algorithms function in various contexts.‎

For training and upskilling employees, courses like the Data Structures and Algorithms Specialization and the Algorithms Specialization are highly recommended. These programs provide a structured approach to learning algorithms, making them suitable for workforce development and enhancing team capabilities in problem-solving and software development.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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