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  • Algorithms

Results for "algorithms"


  • S

    Stanford University

    Algorithms

    Skills you'll gain: Data Structures, Graph Theory, Algorithms, Bioinformatics, Theoretical Computer Science, Social Network Analysis, Network Analysis, Network Routing, Computational Thinking, Mathematical Theory & Analysis, Analysis, Probability & Statistics, Probability, Design Strategies, Computer Science, Logical Reasoning

    Coursera Plus

    Included with Coursera Plus

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

    Intermediate · Specialization · 3 - 6 Months

  • U

    University of California San Diego

    Data Structures and Algorithms

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

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

    Intermediate · Specialization · 3 - 6 Months

  • P

    Princeton University

    Algorithms, Part I

    Skills you'll gain: Data Structures, Algorithms, Graph Theory, Java, Performance Testing, Java Programming, Computational Thinking, Memory Management, Spatial Data Analysis

    4.9
    Rating, 4.9 out of 5 stars
    ·
    12K reviews

    Intermediate · Course · 3 - 6 Months

  • M

    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, Theoretical Computer Science, Scalability

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    Included with Coursera Plus

    4.8
    Rating, 4.8 out of 5 stars
    ·
    36 reviews

    Beginner · Course · 1 - 3 Months

  • P

    Princeton University

    Algorithms, Part II

    Skills you'll gain: Graph Theory, Data Structures, Algorithms, Theoretical Computer Science, Operations Research, Computer Programming, Java Programming, Java

    4.9
    Rating, 4.9 out of 5 stars
    ·
    2.1K reviews

    Intermediate · Course · 3 - 6 Months

  • M

    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, Computer Programming, Graph Theory, Software Design Patterns, Communication

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    4.6
    Rating, 4.6 out of 5 stars
    ·
    818 reviews

    Intermediate · Course · 1 - 4 Weeks

  • U

    University of Colorado Boulder

    Foundations of Data Structures and Algorithms

    Skills you'll gain: Theoretical Computer Science, Algorithms, Graph Theory, Data Structures, Operations Research, Quantum computing, Public Key Cryptography Standards (PKCS), Cryptography, Programming Principles, Computational Thinking, Design Strategies, Cryptographic Protocols, Tree Maps, Encryption, Network Model, Combinatorics, Data Science, Computer Science, Mathematical Modeling, Python Programming

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    Build toward a degree

    4.7
    Rating, 4.7 out of 5 stars
    ·
    967 reviews

    Advanced · Specialization · 3 - 6 Months

  • P

    Packt

    Data Structures and Algorithms: The Complete Masterclass

    Skills you'll gain: Data Structures, Algorithms, Graph Theory, Programming Principles, Theoretical Computer Science, Computer Science, Computer Programming, Python Programming, Pandas (Python Package), Machine Learning Algorithms, Computational Thinking, C++ (Programming Language), Data Architecture, Random Forest Algorithm, Performance Tuning, Object Oriented Programming (OOP), Network Analysis, Program Development, Problem Solving, Debugging

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    4.5
    Rating, 4.5 out of 5 stars
    ·
    39 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: New
    New
    P

    Packt

    Master Data Structures & Algo – Ace Leetcode & Blind 75+

    Skills you'll gain: Data Structures, Graph Theory, Algorithms, Programming Principles, Computational Thinking

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    Intermediate · Specialization · 3 - 6 Months

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    U

    University of London

    Algorithms and Complexity

    Skills you'll gain: Algorithms, Computational Thinking, Theoretical Computer Science, Computational Logic, Critical Thinking and Problem Solving, Performance Testing, Data Structures, Critical Thinking, Logical Reasoning, Graph Theory, Mathematical Theory & Analysis, Complex Problem Solving, Analysis, Game Theory

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    Included with Coursera Plus

    Intermediate · Course · 1 - 4 Weeks

  • P

    Princeton University

    Computer Science: Algorithms, Theory, and Machines

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

    4.7
    Rating, 4.7 out of 5 stars
    ·
    776 reviews

    Intermediate · Course · 1 - 3 Months

  • P

    Princeton University

    Analysis of Algorithms

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

    4.4
    Rating, 4.4 out of 5 stars
    ·
    1.1K reviews

    Advanced · Course · 1 - 3 Months

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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
  • Algorithms, Part II: Princeton University
  • Coding Interview Preparation: Meta
  • Foundations of Data Structures and Algorithms: University of Colorado Boulder
  • Data Structures and Algorithms: The Complete Masterclass: Packt
  • Master Data Structures & Algo – Ace Leetcode & Blind 75+: Packt
  • Algorithms and Complexity: University of London

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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