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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

    • I

      IBM

      IBM DevOps and Software Engineering

      Skills you'll gain: CI/CD, Istio, Open Web Application Security Project (OWASP), Continuous Integration, Software Development Life Cycle, Linux Commands, Agile Software Development, Unit Testing, Cloud Computing Architecture, Application Deployment, Test Driven Development (TDD), Gherkin (Scripting Language), Jenkins, Kubernetes, Bash (Scripting Language), Cloud Services, Git (Version Control System), DevOps, Jupyter, Grafana

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      59K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • 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, System Programming, Data Structures, Software Development, Computer Programming, Command-Line Interface, Development Environment, Development Testing, User Interface (UI), Interactive Design

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

      Beginner · Specialization · 3 - 6 Months

    • Status: New
      New
      I

      IBM

      IBM Java Developer

      Skills you'll gain: Spring Framework, Cloud-Native Computing, Software Development Life Cycle, Hibernate (Java), Docker (Software), Git (Version Control System), GitHub, HTML and CSS, Object Oriented Programming (OOP), Spring Boot, Object-Relational Mapping, Development Environment, Web Design and Development, Object Oriented Design, Java Programming, Generative AI, Interviewing Skills, CI/CD, Java, Professional Networking

      4.7
      Rating, 4.7 out of 5 stars
      ·
      5.3K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • U

      University of Virginia

      Leading the Modern Day Business

      Skills you'll gain: Design Thinking, Digital Transformation, Creative Problem-Solving, New Product Development, Ideation, Business Transformation, Product Management, Technology Strategies, Agile Product Development, Innovation, Creativity, Product Lifecycle Management, Strategic Thinking, Product Improvement, Market Opportunities, Information Technology, Competitive Analysis, Business Analysis, Business Strategy, Cyber Risk

      4.7
      Rating, 4.7 out of 5 stars
      ·
      20K reviews

      Beginner · Specialization · 3 - 6 Months

    • É

      École Polytechnique Fédérale de Lausanne

      Functional Programming in Scala

      Skills you'll gain: Scala Programming, Apache Spark, Apache Hadoop, User Interface (UI), Distributed Computing, Programming Principles, Big Data, Software Design, Data Structures, Software Design Patterns, Functional Design, Data Manipulation, Object Oriented Programming (OOP), Heat Maps, Data Visualization Software, Interactive Data Visualization, Computer Programming, Data Processing, Performance Tuning, Algorithms

      4.7
      Rating, 4.7 out of 5 stars
      ·
      11K reviews

      Intermediate · Specialization · 3 - 6 Months

    • I

      IBM

      Applied Data Science

      Skills you'll gain: Dashboard, Data Visualization Software, Plotly, Data Wrangling, Data Visualization, Interactive Data Visualization, Statistical Reporting, Exploratory Data Analysis, Data Cleansing, Jupyter, Matplotlib, Data Analysis, Pandas (Python Package), Data Manipulation, Seaborn, Data Import/Export, Predictive Modeling, Web Scraping, Automation, Python Programming

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      58K reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      IBM

      IBM Data Analytics with Excel and R

      Skills you'll gain: Data Storytelling, Data Presentation, Interactive Data Visualization, Data Visualization Software, Shiny (R Package), Data Wrangling, Exploratory Data Analysis, Statistical Visualization, Relational Databases, Big Data, Ggplot2, Database Design, Data Analysis, IBM Cognos Analytics, Data Mining, Dashboard, Excel Formulas, Data Manipulation, Web Scraping, Microsoft Excel

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      28K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • I

      IBM

      Cloud Application Development Foundations

      Skills you'll gain: Node.JS, Cloud Computing Architecture, Server Side, Cloud-Native Computing, React Redux, Cloud Services, NoSQL, MongoDB, React.js, Agile Methodology, Front-End Web Development, JavaScript Frameworks, Cloud Security, Hypertext Markup Language (HTML), HTML and CSS, Cloud Infrastructure, Restful API, Web Development, Web Development Tools, Back-End Web Development

      4.6
      Rating, 4.6 out of 5 stars
      ·
      9.8K reviews

      Beginner · Specialization · 3 - 6 Months

    • D

      DeepLearning.AI

      Neural Networks and Deep Learning

      Skills you'll gain: Deep Learning, Artificial Neural Networks, Tensorflow, Supervised Learning, Keras (Neural Network Library), Artificial Intelligence, Machine Learning, Python Programming, NumPy, Performance Tuning

      4.9
      Rating, 4.9 out of 5 stars
      ·
      123K reviews

      Intermediate · Course · 1 - 4 Weeks

    • I

      IBM

      Applied Software Engineering Fundamentals

      Skills you'll gain: Software Development Life Cycle, Linux Commands, Unit Testing, Bash (Scripting Language), Shell Script, Git (Version Control System), GitHub, Development Environment, Version Control, File Management, Jupyter, Software Engineering, Software Architecture, Application Deployment, Automation, Flask (Web Framework), Web Scraping, Python Programming, Open Source Technology, Application Development

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

      Beginner · Specialization · 3 - 6 Months

    • D

      DeepLearning.AI

      Deep Learning

      Skills you'll gain: Computer Vision, Deep Learning, Image Analysis, Natural Language Processing, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Tensorflow, Supervised Learning, Keras (Neural Network Library), Artificial Intelligence, Applied Machine Learning, PyTorch (Machine Learning Library), Machine Learning, Debugging, Performance Tuning, Machine Learning Methods, Python Programming, Data-Driven Decision-Making, Text Mining, Machine Learning Algorithms

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      146K reviews

      Intermediate · 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
      ·
      56K reviews

      Beginner · Specialization · 3 - 6 Months

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

    • IBM DevOps and Software Engineering: IBM
    • Introductory C Programming: Duke University
    • IBM Java Developer: IBM
    • Leading the Modern Day Business: University of Virginia
    • Functional Programming in Scala: École Polytechnique Fédérale de Lausanne
    • Applied Data Science: IBM
    • IBM Data Analytics with Excel and R: IBM
    • Cloud Application Development Foundations: IBM
    • Neural Networks and Deep Learning: DeepLearning.AI
    • Applied Software Engineering Fundamentals: 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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