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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 Minnesota

      Software Development Lifecycle

      Skills you'll gain: User Story, Agile Software Development, Software Design Patterns, Design Thinking, Software Development Methodologies, Software Design, Agile Methodology, Agile Project Management, Engineering Software, Process Mapping, Software Engineering, Kanban Principles, Software Development Life Cycle, Software Quality Assurance, Program Development, Application Security, Scrum (Software Development), Requirements Analysis, Lean Methodologies, Lean Manufacturing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      9.7K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Introduction to HTML5

      Skills you'll gain: Hypertext Markup Language (HTML), Web Content Accessibility Guidelines, Web Design and Development, Usability, Semantic Web, Cascading Style Sheets (CSS), Cloud Hosting, Web Servers, Data Validation, Web Development Tools

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

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      Digital Transformation Using AI/ML with Google Cloud

      Skills you'll gain: Serverless Computing, Digital Transformation, Cloud Services, Data Ethics, Cloud Infrastructure, Google Cloud Platform, Application Programming Interface (API), Applied Machine Learning, Hybrid Cloud Computing, Infrastructure As A Service (IaaS), Cloud Computing, Public Cloud, Technical Management, Business Transformation, Containerization, Technology Strategies, Cloud-Native Computing, Multi-Cloud, IT Management, Machine Learning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7.4K reviews

      Beginner · Specialization · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      IBM Machine Learning

      Skills you'll gain: Exploratory Data Analysis, Unsupervised Learning, Supervised Learning, Feature Engineering, Generative AI, Regression Analysis, Dimensionality Reduction, Reinforcement Learning, Data Cleansing, Data Access, Deep Learning, Data Analysis, Applied Machine Learning, Predictive Modeling, Statistical Analysis, Statistical Inference, Statistical Hypothesis Testing, Machine Learning Algorithms, Classification And Regression Tree (CART), Scikit Learn (Machine Learning Library)

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      3.1K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Alberta

      Software Product Management

      Skills you'll gain: Requirements Analysis, Agile Software Development, Agile Methodology, Kanban Principles, Project Planning, Requirements Elicitation, Sprint Retrospectives, Requirements Management, Functional Requirement, Business Requirements, Sprint Planning, Software Development Methodologies, Software Development Life Cycle, Scrum (Software Development), Software Technical Review, Code Review, Software Development, Product Requirements, Risk Management Framework, User Story

      4.7
      Rating, 4.7 out of 5 stars
      ·
      12K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Alberta

      Prediction and Control with Function Approximation

      Skills you'll gain: Reinforcement Learning, Deep Learning, Machine Learning Algorithms, Machine Learning, Supervised Learning, Artificial Neural Networks, Pseudocode, Linear Algebra, Probability Distribution

      4.8
      Rating, 4.8 out of 5 stars
      ·
      836 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Data Visualization with Python

      Skills you'll gain: Data Visualization Software, Plotly, Data Visualization, Dashboard, Interactive Data Visualization, Matplotlib, Seaborn, Data Presentation, Data Analysis, Geospatial Information and Technology, Pandas (Python Package), Scatter Plots, Histogram, Heat Maps, Box Plots

      4.5
      Rating, 4.5 out of 5 stars
      ·
      12K reviews

      Intermediate · Course · 1 - 3 Months

    • S

      Stanford University

      Cryptography I

      Skills you'll gain: Cryptography, Data Encryption Standard, Encryption, Key Management, Advanced Encryption Standard (AES), Public Key Cryptography Standards (PKCS), Cybersecurity, Authentications, Data Integrity, Secure Coding, Algorithms

      4.8
      Rating, 4.8 out of 5 stars
      ·
      4.4K reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      G

      Google

      Automate Cybersecurity Tasks with Python

      Skills you'll gain: Debugging, Python Programming, Cybersecurity, Cyber Security Assessment, Scripting, Programming Principles, Algorithms, Automation, Integrated Development Environments, File Management, Data Structures

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.1K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      T

      The Hong Kong University of Science and Technology

      Mathematics for Engineers

      Skills you'll gain: Differential Equations, Linear Algebra, Matlab, Engineering Calculations, Engineering Analysis, Numerical Analysis, Finite Element Methods, Integral Calculus, Mathematical Software, Mechanical Engineering, Calculus, Algebra, Applied Mathematics, Mathematical Modeling, Engineering, Simulation and Simulation Software, Advanced Mathematics, Geometry, Computational Thinking, Estimation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      7.5K reviews

      Beginner · Specialization · 3 - 6 Months

    • P

      Pontificia Universidad Católica de Chile

      Introducción a la programación en Python I: Aprendiendo a programar con Python

      Skills you'll gain: Python Programming, Data Structures, Computer Programming, Program Development, Application Development, Algorithms, File Management

      4.4
      Rating, 4.4 out of 5 stars
      ·
      4.8K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Toronto

      Self-Driving Cars

      Skills you'll gain: Computer Vision, Image Analysis, Control Systems, Embedded Software, Automation, Deep Learning, Software Architecture, Computer Graphics, Simulations, Safety Assurance, Artificial Neural Networks, Global Positioning Systems, Visualization (Computer Graphics), Hardware Architecture, Estimation, Algorithms, Machine Learning Methods, Predictive Modeling, Scenario Testing, Spatial Data Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.5K reviews

      Advanced · Specialization · 3 - 6 Months

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

    • Software Development Lifecycle: University of Minnesota
    • Introduction to HTML5: University of Michigan
    • Digital Transformation Using AI/ML with Google Cloud: Google Cloud
    • IBM Machine Learning: IBM
    • Software Product Management: University of Alberta
    • Prediction and Control with Function Approximation: University of Alberta
    • Data Visualization with Python: IBM
    • Cryptography I: Stanford University
    • Automate Cybersecurity Tasks with Python: Google
    • Mathematics for Engineers: The Hong Kong University of Science and Technology

    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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