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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

    • 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, Data Analysis, Computer Programming, Programming Principles, Data Processing, Application Development, Data Structures, Scripting, Debugging, Mathematical Software, Data Manipulation

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

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Washington

      Dynamic Public Speaking

      Skills you'll gain: Public Speaking, Persuasive Communication, Presentations, Verbal Communication Skills, Communication, Storytelling, Motivational Skills, Communication Strategies, Writing, Data Visualization, Constructive Feedback, Target Audience, Non-Verbal Communication, Composure, Planning, Leadership, Analysis, Stress Management, Self-Awareness, Organizational Skills

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.7K reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      IBM

      Data Engineering Foundations

      Skills you'll gain: SQL, Web Scraping, Database Design, MySQL, Data Transformation, Extract, Transform, Load, IBM DB2, Relational Databases, Data Architecture, Jupyter, Data Pipelines, Big Data, Database Management, Data Warehousing, Data Governance, Databases, Stored Procedure, Data Manipulation, Automation, Python Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      54K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: [object Object]
      AI skills
      I

      IBM

      IBM Data Analyst

      Skills you'll gain: Data Storytelling, Dashboard, Data Visualization Software, Plotly, Data Presentation, Data Wrangling, Data Visualization, SQL, Generative AI, Interactive Data Visualization, Exploratory Data Analysis, Data Cleansing, Big Data, Jupyter, Matplotlib, Data Analysis, Statistical Analysis, Pandas (Python Package), Excel Formulas, Professional Networking

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      89K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • I

      IBM

      IBM Back-End Development

      Skills you'll gain: Open Web Application Security Project (OWASP), Istio, Software Development Life Cycle, Linux Commands, Unit Testing, Application Deployment, Kubernetes, NoSQL, Bash (Scripting Language), MongoDB, Shell Script, Django (Web Framework), Object-Relational Mapping, OpenShift, Git (Version Control System), Cloud Applications, Containerization, GitHub, Jupyter, Grafana

      4.6
      Rating, 4.6 out of 5 stars
      ·
      47K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • B

      Birla Institute of Technology & Science, Pilani

      Introduction to Programming

      Skills you'll gain: Programming Principles, C (Programming Language), Computer Hardware, Computer Programming, Computer Architecture, Computer Systems, Computational Thinking, Data Structures, Algorithms, File Management, Program Development, Data Storage, Debugging

      Build toward a degree

      4.5
      Rating, 4.5 out of 5 stars
      ·
      46 reviews

      Beginner · Course · 1 - 3 Months

    • Placeholder
      J

      Johns Hopkins University

      Data Science: Foundations using R

      Skills you'll gain: Rmarkdown, Exploratory Data Analysis, Version Control, Statistical Analysis, R Programming, Data Manipulation, Data Cleansing, Data Science, Data Visualization, Statistical Programming, Ggplot2, Dimensionality Reduction, Data Visualization Software, Data Integration, Knitr, Data Analysis, Data Import/Export, General Science and Research, Data Sharing, Statistical Reporting

      4.6
      Rating, 4.6 out of 5 stars
      ·
      48K reviews

      Beginner · Specialization · 3 - 6 Months

    • Placeholder
      U

      University of California San Diego

      Object Oriented Programming in Java

      Skills you'll gain: Event-Driven Programming, Interactive Data Visualization, Java, Java Programming, Object Oriented Programming (OOP), User Interface (UI), Computer Programming, Algorithms, Graphical Tools, Software Engineering, Data Structures, Programming Principles, Software Documentation, Development Environment, Debugging

      4.7
      Rating, 4.7 out of 5 stars
      ·
      5.8K reviews

      Intermediate · Course · 1 - 3 Months

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      I
      U
      I

      Multiple educators

      Data Science Foundations

      Skills you'll gain: Dashboard, Pseudocode, Jupyter, Algorithms, Data Mining, Pandas (Python Package), Data Visualization Software, Correlation Analysis, Web Scraping, NumPy, R Programming, Probability & Statistics, Predictive Modeling, Big Data, Automation, Computer Programming Tools, GitHub, Data Analysis Software, Machine Learning Algorithms, Unsupervised Learning

      4.6
      Rating, 4.6 out of 5 stars
      ·
      111K reviews

      Beginner · Specialization · 3 - 6 Months

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      U

      University of London

      Object Oriented Programming

      Skills you'll gain: Pseudocode, C++ (Programming Language), Object Oriented Programming (OOP), Object Oriented Design, Computer Programming, Development Environment, Programming Principles, Debugging, Data Structures, Algorithms, Interactive Design, Program Development, Data Modeling, Test Data, User Interface (UI), Command-Line Interface, Statistical Programming, Development Testing, Transaction Processing, File Management

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      213 reviews

      Intermediate · Specialization · 1 - 3 Months

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      É

      École Polytechnique Fédérale de Lausanne

      Functional Programming Principles in Scala

      Skills you'll gain: Scala Programming, Programming Principles, Object Oriented Programming (OOP), Functional Design, Software Design Patterns, Computer Programming, Data Structures, Software Engineering, Javascript, Algorithms, Computational Thinking

      4.8
      Rating, 4.8 out of 5 stars
      ·
      8.2K reviews

      Intermediate · Course · 1 - 3 Months

    • Placeholder
      U

      University of Pennsylvania

      Introduction to Programming with Python and Java

      Skills you'll gain: Matplotlib, Object Oriented Design, Java, Object Oriented Programming (OOP), Data Analysis, Unit Testing, Pandas (Python Package), Java Programming, Eclipse (Software), Data Structures, Data Science, Data Cleansing, Debugging, Pivot Tables And Charts, Data Visualization Software, Integrated Development Environments, Programming Principles, Python Programming, Computer Programming, Computational Thinking

      4.5
      Rating, 4.5 out of 5 stars
      ·
      1.8K reviews

      Beginner · Specialization · 3 - 6 Months

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

    • MATLAB Programming for Engineers and Scientists: Vanderbilt University
    • Dynamic Public Speaking: University of Washington
    • Data Engineering Foundations: IBM
    • IBM Data Analyst: IBM
    • IBM Back-End Development: IBM
    • Introduction to Programming: Birla Institute of Technology & Science, Pilani
    • Data Science: Foundations using R: Johns Hopkins University
    • Object Oriented Programming in Java: University of California San Diego
    • Data Science Foundations: IBM
    • Object Oriented Programming: University of London

    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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