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    • Dynamic Programming

    Dynamic Programming Courses Online

    Master dynamic programming techniques for solving complex problems. Learn to break down problems into simpler subproblems for efficient solutions.

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    Explore the Dynamic Programming Course Catalog

    • Status: Free Trial
      Free Trial
      U

      University of California San Diego

      Introduction to Discrete Mathematics for Computer Science

      Skills you'll gain: Graph Theory, Logical Reasoning, Combinatorics, Computational Logic, Deductive Reasoning, Cryptography, Probability, Key Management, Computational Thinking, Encryption, Network Analysis, Public Key Cryptography Standards (PKCS), Algorithms, Theoretical Computer Science, Python Programming, Data Structures, Cybersecurity, Arithmetic, Computer Programming, Mathematical Modeling

      4.5
      Rating, 4.5 out of 5 stars
      ·
      3.6K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Advanced R Programming

      Skills you'll gain: Object Oriented Programming (OOP), R Programming, Debugging, Functional Design, Programming Principles, Data Manipulation, Data Structures, Software Design Patterns, Performance Tuning

      4.2
      Rating, 4.2 out of 5 stars
      ·
      574 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of California, Irvine

      Programming with Google Go

      Skills you'll gain: Go (Programming Language), Object Oriented Programming (OOP), Algorithms, JSON, Programming Principles, OS Process Management, Functional Design, Data Structures, Other Programming Languages, System Programming, Development Environment, Software Design, Remote Access Systems, Software Installation, Operating Systems, File Management, Program Development, Computer Architecture

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.9K reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Colorado Boulder

      Control Systems Analysis: Modeling of Dynamic Systems

      Skills you'll gain: Control Systems, Mathematical Modeling, Engineering Analysis, Differential Equations, Engineering Calculations, Systems Analysis, Electrical Systems, Mechanics, Applied Mathematics, Basic Electrical Systems

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      85 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      D

      Duke University

      Data Analysis with R

      Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Statistical Inference, Exploratory Data Analysis, Regression Analysis, Statistical Reporting, Probability Distribution, Statistical Methods, Data Analysis Software, R Programming, Bayesian Statistics, Statistical Analysis, Data Analysis, Statistical Software, Statistical Modeling, Probability & Statistics, Probability, Statistics, Correlation Analysis, Data Literacy

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7.5K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      L

      LearnQuest

      Core Java

      Skills you'll gain: Java Programming, Spring Framework, Java, Eclipse (Software), Object Oriented Programming (OOP), Object Oriented Design, Integrated Development Environments, Development Environment, Java Platform Enterprise Edition (J2EE), Software Design, Software Installation, Computer Programming, Programming Principles, Program Development, Virtual Machines, Debugging, Package and Software Management, Data Structures, File Management

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.7K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      D

      Duke University

      Introductory C Programming

      Skills you'll gain: Debugging, Maintainability, Programming Principles, Algorithms, Software Testing, Program Development, C (Programming Language), Pseudocode, Computational Thinking, Software Engineering, Simulations, Test Case, System Programming, Data Structures, Software Development, Computer Programming, Command-Line Interface, Operating Systems, Development Environment, User Interface (UI)

      4.6
      Rating, 4.6 out of 5 stars
      ·
      7.3K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Alberta

      Fundamentals of Reinforcement Learning

      Skills you'll gain: Reinforcement Learning, Machine Learning, Machine Learning Algorithms, Artificial Intelligence, Markov Model, Algorithms, Probability Distribution

      4.8
      Rating, 4.8 out of 5 stars
      ·
      2.8K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of California, Irvine

      Career Success

      Skills you'll gain: Business Writing, Time Management, Goal Setting, Negotiation, Cash Management, Business Planning, Planning, Project Controls, Feasibility Studies, Delegation Skills, Leadership and Management, Team Leadership, Business Correspondence, Creative Problem-Solving, Problem Solving, Professional Networking, Financial Analysis, Communication Strategies, Communication, Emotional Intelligence

      4.6
      Rating, 4.6 out of 5 stars
      ·
      44K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      D

      Duke University

      Java Programming and Software Engineering Fundamentals

      Skills you'll gain: Object Oriented Programming (OOP), Java, Hypertext Markup Language (HTML), Software Design, Software Design Patterns, Data Structures, HTML and CSS, Debugging, Software Engineering, Cascading Style Sheets (CSS), Web Development, Computer Programming, Programming Principles, Javascript, Encryption, Algorithms, AI Personalization, Web Design, Data Processing, Statistical Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      22K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      B

      Board Infinity

      Fundamentals of Java Programming

      Skills you'll gain: Eclipse (Software), Object Oriented Programming (OOP), Java Programming, Object Oriented Design, Software Development Tools, Java, Integrated Development Environments, Development Environment, Computer Programming, Programming Principles, Data Structures, Virtual Machines

      4.4
      Rating, 4.4 out of 5 stars
      ·
      509 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of California San Diego

      Algorithmic Toolbox

      Skills you'll gain: Algorithms, Program Development, Debugging, Development Testing, Test Engineering, Software Testing, Computational Thinking, Test Case, Computer Programming, Programming Principles, Data Structures, Theoretical Computer Science, Bioinformatics, Design Strategies

      4.6
      Rating, 4.6 out of 5 stars
      ·
      13K reviews

      Intermediate · Course · 1 - 3 Months

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    In summary, here are 10 of our most popular dynamic programming courses

    • Introduction to Discrete Mathematics for Computer Science: University of California San Diego
    • Advanced R Programming: Johns Hopkins University
    • Programming with Google Go: University of California, Irvine
    • Control Systems Analysis: Modeling of Dynamic Systems: University of Colorado Boulder
    • Data Analysis with R: Duke University
    • Core Java: LearnQuest
    • Introductory C Programming: Duke University
    • Fundamentals of Reinforcement Learning: University of Alberta
    • Career Success: University of California, Irvine
    • Java Programming and Software Engineering Fundamentals: Duke University

    Skills you can learn in Business Strategy

    Modeling (25)
    Market (economics) (21)
    Plan (19)
    Planning (16)
    Strategic Management (16)
    Business Model (13)
    Operations Management (13)
    Analytics (12)
    Evaluation (12)
    Project Management (11)
    Supply Chain (10)
    Decision-making (9)

    Frequently Asked Questions about Dynamic Programming

    Dynamic programming is an algorithmic technique that solves optimization problems by breaking them down into simpler sub-problems. The solutions to these sub-problems are stored along the way, which ensures that each problem is only solved once. Dynamic programming has become an important technique for efficiently solving complex optimization problems in applications such as reinforcement learning for artificial intelligence (AI) and genome sequencing in bioinformatics.

    The advantages of dynamic programming can be understood in relation to other algorithms used to solve optimization problems. Like divide and conquer algorithms, dynamic programming breaks down a larger problem into smaller pieces; however, unlike divide and conquer, it saves solutions along the way so each problem is only solved once, improving the speed of this approach. By contrast, greedy algorithms also solve each problem only once, but unlike dynamic programming, it does not look back to consider all possible solutions, running the risk that the greedy algorithm will settle on a locally optimal solution that is not globally optimal.

    Ultimately, there is no single “silver bullet” algorithm that is best for every application, and different types of problems will require different techniques. However, dynamic programming’s ability to deliver globally optimal solutions with relative efficiency makes it an important part of any programmer’s skill set.‎

    Dynamic programming is a valuable career skill for programmers working on complex optimization problems in high-tech fields such as data science, artificial intelligence and machine learning, robotics, and bioinformatics. Computer scientists with the ability to find the right approaches to these high-value problems are highly sought after and compensated accordingly by leading companies in these industries. According to the Bureau of Labor Statistics, computer and information research scientists earned a median annual salary of $122,840 per year in 2019, and these jobs are expected to grow much faster than the average across the rest of the economy.‎

    Yes! There are an incredibly wide range of learning opportunities in computer science on Coursera, including courses and Specializations in algorithms and dynamic programming. Coursera lets you learn about dynamic programming remotely from top-ranked universities from around the world such as Stanford University, National Research University Higher School of Economics, and University of Alberta. And, because learners on Coursera pay a significantly lower tuition than on-campus students, you won’t need to use dynamic programming or other algorithmic techniques to determine whether it’s an optimal investment in your career.‎

    The people best suited for roles in dynamic programming are computer programmers and people with experience working with algorithms. Dynamic programming is an algorithmic technique for breaking down a problem into simpler subproblems, so it’s important that people who pursue roles in dynamic programming have experience working in fields that utilize this technique. People who work as aerospace engineers or in economics are best suited for these roles.‎

    A common career path for someone in dynamic programming is a job as a computer and information research scientist. These scientists design software systems and invent new computing languages, which they later test and present to colleagues in academic journals and conferences. Another common career path for someone studying dynamic programming is working with robotics or in computer programming.‎

    It’s important for learners to have a strong handle on algorithms, so topics related to advanced algorithms and complexity, discrete optimization, data structures and algorithms, algorithms on strings, and algorithms on graphs are extremely useful. Reinforcement learning may explore topics related to AI tools and how it is useful in game development, customer interaction, and supply chain. For learners looking to improve their computer programming skills, the fundamentals of computing may help you program and think like a computer scientist. Competitive programming is the next step up and is a great option if you want to explore topics related to dynamic programming and number and graph theories.‎

    Most people with a background in dynamic programming are hired to work in the federal government, according to the U.S. Bureau of Labor Statistics. Some people also work for computer systems and design-related services companies. Research and development companies hire people with a background in dynamic programming as well as software publishers.‎

    Online Dynamic Programming courses offer a convenient and flexible way to enhance your knowledge or learn new Dynamic Programming skills. Choose from a wide range of Dynamic Programming courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in Dynamic Programming, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

    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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