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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
      G

      Google

      Crash Course on Python

      Skills you'll gain: Programming Principles, Python Programming, Computer Programming, Computational Thinking, Algorithms, Problem Management, Data Structures, Integrated Development Environments, Debugging, Development Environment

      4.8
      Rating, 4.8 out of 5 stars
      ·
      39K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      GPU Programming

      Skills you'll gain: Artificial Neural Networks, Image Analysis, Event-Driven Programming, C and C++, Scalability, Deep Learning, Software Development, Machine Learning Methods, Performance Tuning, Linear Algebra, Distributed Computing, System Programming, Computer Graphics, Computer Hardware, Computer Vision, Numerical Analysis, Computer Architecture, Data Processing, Data Structures, Performance Testing

      Build toward a degree

      2.7
      Rating, 2.7 out of 5 stars
      ·
      151 reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of California, Irvine

      Career Success

      Skills you'll gain: Time Management, Business Writing, Goal Setting, Negotiation, Cash Management, Business Planning, Planning, Project Controls, Feasibility Studies, Delegation Skills, Entrepreneurship, 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: New
      New
      Status: Free Trial
      Free Trial
      M

      Meta

      Meta Full-Stack Developer

      Skills you'll gain: Jest (JavaScript Testing Framework), Django (Web Framework), Version Control, Restful API, Responsive Web Design, Unix Commands, HTML and CSS, Git (Version Control System), GitHub, Relational Databases, Object Oriented Programming (OOP), Database Management Systems, Bootstrap (Front-End Framework), React.js, Mobile Development, SQL, Database Design, Unit Testing, Web Development Tools, Web Development

      4.7
      Rating, 4.7 out of 5 stars
      ·
      23K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      M

      Meta

      Programming with JavaScript

      Skills you'll gain: Jest (JavaScript Testing Framework), Web Development Tools, Javascript, Unit Testing, Object Oriented Programming (OOP), Node.JS, JSON, Computer Programming, Data Structures, Debugging, Package and Software Management, Functional Design

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

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Python 3 Programming

      Skills you'll gain: Unified Modeling Language, JSON, Object Oriented Programming (OOP), Software Design, Debugging, Object Oriented Design, Data Processing, Web Scraping, Unit Testing, Programming Principles, Data Import/Export, Restful API, Python Programming, Image Analysis, Data Manipulation, Jupyter, Maintainability, Data Structures, Software Engineering, File Management

      4.8
      Rating, 4.8 out of 5 stars
      ·
      23K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      R Programming

      Skills you'll gain: Statistical Analysis, R Programming, Statistical Programming, Data Analysis, Debugging, Simulations, Computer Programming Tools, Program Development, Data Structures, Performance Tuning, Data Import/Export

      4.5
      Rating, 4.5 out of 5 stars
      ·
      22K reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      I

      IBM

      Introduction to R Programming for Data Science

      Skills you'll gain: Data Manipulation, Web Scraping, R Programming, Data Analysis, Data Science, Data Structures, Data Import/Export, Exploratory Data Analysis, Programming Principles, Jupyter, Integrated Development Environments

      4.5
      Rating, 4.5 out of 5 stars
      ·
      567 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      D
      U

      Multiple educators

      Object Oriented Programming in Java

      Skills you'll gain: Unit Testing, Data Structures, Event-Driven Programming, Interactive Data Visualization, Java, Object Oriented Programming (OOP), Development Testing, User Interface (UI), Debugging, Java Programming, Software Testing, Computer Programming, Software Engineering, Algorithms, Performance Tuning, Encryption, Programming Principles, Data Analysis, Statistical Analysis, Software Design

      4.6
      Rating, 4.6 out of 5 stars
      ·
      15K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Data Analysis with R

      Skills you'll gain: Data Wrangling, Exploratory Data Analysis, Data Analysis, Data Transformation, R Programming, Data Manipulation, Data Visualization, Box Plots, Predictive Analytics, Statistical Analysis, Regression Analysis, Statistical Modeling, Correlation Analysis, Data Cleansing, Tidyverse (R Package), Supervised Learning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      335 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      V

      Vanderbilt University

      MATLAB Programming for Engineers and Scientists

      Skills you'll gain: Data Visualization, Image Analysis, Data Visualization Software, Matlab, Machine Learning Methods, Algorithms, User Interface (UI), Applied Machine Learning, Object Oriented Programming (OOP), Statistical Methods, Mathematical Software, Engineering Calculations, Data Analysis, Data Processing, Engineering Analysis, Computer Programming, Programming Principles, UI Components, Software Design, Debugging

      4.8
      Rating, 4.8 out of 5 stars
      ·
      18K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      C Programming for Everybody

      Skills you'll gain: C (Programming Language), C++ (Programming Language), Object Oriented Programming (OOP), Data Structures, Programming Principles, Algorithms, Computer Programming, Software Design, Application Security, Other Programming Languages, Python Programming, System Programming, Java, Performance Tuning, Numerical Analysis, Unix, Computer Science, Debugging

      4.5
      Rating, 4.5 out of 5 stars
      ·
      163 reviews

      Intermediate · Specialization · 3 - 6 Months

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

    • Crash Course on Python: Google
    • GPU Programming: Johns Hopkins University
    • Career Success: University of California, Irvine
    • Meta Full-Stack Developer: Meta
    • Programming with JavaScript: Meta
    • Python 3 Programming: University of Michigan
    • R Programming: Johns Hopkins University
    • Introduction to R Programming for Data Science: IBM
    • Object Oriented Programming in Java: Duke University
    • Data Analysis with R: IBM

    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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