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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

    • U

      University of Pennsylvania

      Finance & Quantitative Modeling for Analysts

      Skills you'll gain: Return On Investment, Financial Reporting, Finance, Financial Data, Capital Budgeting, Financial Statements, Financial Modeling, Mathematical Modeling, Statistical Modeling, Regression Analysis, Business Modeling, Income Statement, Financial Analysis, Risk Analysis, Cash Flows, Business Mathematics, Financial Planning, Spreadsheet Software, Google Sheets, Excel Formulas

      4.5
      Rating, 4.5 out of 5 stars
      ·
      17K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: New AI skills
      New AI skills
      G

      Google

      Google Cybersecurity

      Skills you'll gain: Threat Modeling, Network Security, Incident Response, Vulnerability Management, Computer Security Incident Management, Hardening, Stakeholder Communications, Intrusion Detection and Prevention, Cyber Threat Intelligence, Threat Management, Cybersecurity, Network Protocols, Vulnerability Assessments, Network Architecture, Event Monitoring, Bash (Scripting Language), Operating Systems, Security Controls, Debugging, Python Programming

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      50K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • V

      Vanderbilt University

      Introduction to Programming with MATLAB

      Skills you'll gain: Matlab, Computer Programming, Programming Principles, Debugging, Mathematical Software, Data Manipulation, Computer Science, Algorithms, Data Import/Export, Data Structures, Linear Algebra, Engineering Calculations, Graphing

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

      Beginner · Course · 1 - 3 Months

    • G

      Google

      Google AI Essentials

      Skills you'll gain: Generative AI, Artificial Intelligence and Machine Learning (AI/ML), Productivity Software, Artificial Intelligence, Data Ethics, Security Awareness, Business Workflow Analysis, Innovation, Automation, Workflow Management, Information Privacy, Human Computer Interaction, Content Creation, Natural Language Processing, Complex Problem Solving

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

      Beginner · Course · 1 - 3 Months

    • U

      University of California, Santa Cruz

      C for Everyone: Programming Fundamentals

      Skills you'll gain: Debugging, C (Programming Language), Programming Principles, Data Structures, Computer Programming, Program Development, Computer Science, Computational Thinking, Algorithms, System Programming

      4.5
      Rating, 4.5 out of 5 stars
      ·
      6.6K reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of California, Irvine

      The Arduino Platform and C Programming

      Skills you'll gain: Embedded Software, Embedded Systems, Debugging, C (Programming Language), Integrated Development Environments, Program Development, Development Environment, Computer Hardware, Computer Programming, Digital Communications, Open Source Technology

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7.1K reviews

      Mixed · Course · 1 - 4 Weeks

    • D

      Duke University

      Java Programming and Software Engineering Fundamentals

      Skills you'll gain: Object Oriented Programming (OOP), Java, Hypertext Markup Language (HTML), Software Design, Data Structures, Debugging, Web Design and Development, Software Engineering, Cryptography, Cascading Style Sheets (CSS), Web Development, Programming Principles, Javascript, Encryption, Algorithms, Program Development, Web Applications, Front-End Web Development, Statistical Analysis, Computer Programming

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

      Beginner · Specialization · 3 - 6 Months

    • Status: AI skills
      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
      ·
      91K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • I

      IBM

      IBM AI Developer

      Skills you'll gain: Generative AI, Software Development Life Cycle, Unit Testing, ChatGPT, HTML and CSS, Development Environment, Web Design and Development, Jupyter, Hypertext Markup Language (HTML), Software Engineering, Artificial Intelligence, Cascading Style Sheets (CSS), Web Development, Data Ethics, Application Deployment, Web Applications, Automation, Interviewing Skills, CI/CD, Professional Networking

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      68K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: New
      New
      I

      IBM

      IBM Relational Database Administrator

      Skills you'll gain: Data Warehousing, SQL, Extract, Transform, Load, Apache Airflow, Web Scraping, Linux Commands, Database Design, Database Administration, MySQL, Data Pipelines, Apache Kafka, Database Management, Bash (Scripting Language), Shell Script, Database Architecture and Administration, Data Transformation, IBM DB2, Relational Databases, Jupyter, Generative AI

      4.6
      Rating, 4.6 out of 5 stars
      ·
      57K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • 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, Peer Review, 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

    • U

      University of Alberta

      Reinforcement Learning

      Skills you'll gain: Reinforcement Learning, Machine Learning, Sampling (Statistics), Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Machine Learning Algorithms, Deep Learning, Systems Development, Simulations, Solution Architecture, Markov Model, Supervised Learning, Artificial Neural Networks, Applied Machine Learning, Performance Testing, Algorithms, Statistical Methods, Pseudocode, Linear Algebra, Probability Distribution

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

      Intermediate · Specialization · 3 - 6 Months

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

    • Finance & Quantitative Modeling for Analysts: University of Pennsylvania
    • Google Cybersecurity: Google
    • Introduction to Programming with MATLAB: Vanderbilt University
    • Google AI Essentials: Google
    • C for Everyone: Programming Fundamentals: University of California, Santa Cruz
    • The Arduino Platform and C Programming: University of California, Irvine
    • Java Programming and Software Engineering Fundamentals: Duke University
    • IBM Data Analyst: IBM
    • IBM AI Developer: IBM
    • IBM Relational Database Administrator: 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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