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    • Linear Programming

    Linear Programming Courses Online

    Learn linear programming for optimizing resources and solving problems. Understand algorithms, simplex method, and practical applications.

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    Explore the Linear Programming Course Catalog

    • IBM

      Data Science Fundamentals with Python and SQL

      Skills you'll gain: Dashboard, SQL, Descriptive Statistics, Jupyter, Statistical Analysis, Data Analysis, Probability Distribution, Pandas (Python Package), Data Visualization Software, Statistics, Data Visualization, Web Scraping, Relational Databases, Stored Procedure, Databases, Computer Programming Tools, Automation, Data Analysis Software, Data Science, Python Programming

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      71K reviews

      Beginner · Specialization · 3 - 6 Months

    • 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, Operating Systems, Development Environment, User Interface (UI), Data Import/Export

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

      Beginner · Specialization · 3 - 6 Months

    • DeepLearning.AI

      Deep Learning

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

      Build toward a degree

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

      Intermediate · Specialization · 3 - 6 Months

    • 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 Development Tools, Application Deployment, Collaborative Software, Automation, Flask (Web Framework), Web Scraping, Python Programming, Software Testing

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

      Beginner · Specialization · 3 - 6 Months

    • Johns Hopkins University

      Linear Algebra: Linear Systems and Matrix Equations

      Skills you'll gain: Linear Algebra, Algebra, Mathematical Modeling, Engineering Analysis, Applied Mathematics, Mathematical Theory & Analysis, Geometry

      4.7
      Rating, 4.7 out of 5 stars
      ·
      136 reviews

      Beginner · Course · 1 - 4 Weeks

    • IBM

      Introduction to Data Science

      Skills you'll gain: SQL, Jupyter, Data Literacy, Data Mining, Peer Review, Data Modeling, Relational Databases, Stored Procedure, Databases, Data Science, Big Data, Computer Programming Tools, Query Languages, Data Analysis Software, Data Cleansing, GitHub, Business Analysis, Cloud Computing, Data Analysis, Digital Transformation

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      98K reviews

      Beginner · Specialization · 3 - 6 Months

    • Duke University

      Java Programming and Software Engineering Fundamentals

      Skills you'll gain: Object Oriented Programming (OOP), Java, Hypertext Markup Language (HTML), Software Design, Software Design Patterns, Data Structures, HTML and CSS, Debugging, Software Engineering, Cascading Style Sheets (CSS), Web Development, Computer Programming, Programming Principles, Javascript, Encryption, Algorithms, AI Personalization, Web Design, Data Processing, Statistical Analysis

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

      Beginner · Specialization · 3 - 6 Months

    • IBM

      Data Engineering Foundations

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

      4.6
      Rating, 4.6 out of 5 stars
      ·
      56K reviews

      Beginner · Specialization · 3 - 6 Months

    • Johns Hopkins University

      Data Science

      Skills you'll gain: Shiny (R Package), Rmarkdown, Exploratory Data Analysis, Regression Analysis, Leaflet (Software), Version Control, Statistical Analysis, R Programming, Data Manipulation, Data Cleansing, Data Science, Statistical Inference, Statistical Hypothesis Testing, Predictive Modeling, Data Wrangling, Data Visualization, Plotly, Machine Learning Algorithms, Plot (Graphics), Knitr

      4.5
      Rating, 4.5 out of 5 stars
      ·
      51K reviews

      Beginner · Specialization · 3 - 6 Months

    • IBM

      AI Foundations for Everyone

      Skills you'll gain: Prompt Engineering, ChatGPT, Large Language Modeling, Generative AI, Artificial Intelligence, Data Ethics, Artificial Intelligence and Machine Learning (AI/ML), OpenAI, IBM Cloud, Private Cloud, Data Loss Prevention, Applied Machine Learning, Deep Learning, WordPress, Artificial Neural Networks, Governance, Machine Learning, Generative AI Agents, Automation, Digital Transformation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      27K reviews

      Beginner · Specialization · 3 - 6 Months

    • Duke University

      Data Analysis with R

      Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Statistical Inference, Exploratory Data Analysis, Regression Analysis, Statistical Reporting, Probability Distribution, Statistical Methods, Data Analysis Software, R Programming, Bayesian Statistics, Statistical Analysis, Data Analysis, Statistical Software, Statistical Modeling, Probability & Statistics, Probability, Statistics, Correlation Analysis, Data Literacy

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7.5K reviews

      Beginner · Specialization · 3 - 6 Months

    • DeepLearning.AI

      Linear Algebra for Machine Learning and Data Science

      Skills you'll gain: Linear Algebra, NumPy, Dimensionality Reduction, Machine Learning Methods, Jupyter, Data Manipulation, Data Science, Applied Mathematics, Python Programming, Image Analysis, Artificial Intelligence

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2K reviews

      Intermediate · Course · 1 - 4 Weeks

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    1…456…305

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

    • Data Science Fundamentals with Python and SQL: IBM
    • Introductory C Programming: Duke University
    • Deep Learning: DeepLearning.AI
    • Applied Software Engineering Fundamentals: IBM
    • Linear Algebra: Linear Systems and Matrix Equations: Johns Hopkins University
    • Introduction to Data Science: IBM
    • Java Programming and Software Engineering Fundamentals: Duke University
    • Data Engineering Foundations: IBM
    • Data Science: Johns Hopkins University
    • AI Foundations for Everyone: IBM

    Skills you can learn in Business Essentials

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    Business Communication (16)
    Decision-making (16)
    Leadership (15)

    Frequently Asked Questions about Linear Programming

    Learn about linear programming if you want to be able to use more tools for data modeling and analysis. Linear programming is a mathematical technique. It's used to maximize or minimize a linear function, similar to a regression, that includes such variables as production output or inventory cost. It is related to regression analysis. Linear programming can be used to solve problems in the face of different restraints. Linear programming can help you pull insights and make decisions from the information that's been collecting for a long time. It's used in financial analysis, financial modeling, and strategic planning. It's often part of algorithms written by computer programmers, too, although it does not necessarily require computer programming to learn it.‎

    Career opportunities that arise from learning linear programming are mostly in computer programming, financial analysis, and quantitative data modeling. It can be applied to any field where data is generated, resources are limited, and decisions have to be made. Also, it is important to understand that the role of linear programming generates results with discrete optimization so that the outcomes are used effectively. It is also useful to understand the power and limitations of linear programming if you will be using reports and making decisions based on its results. It is a powerful component of computer programs that include advanced algorithms or game theory.‎

    Online courses on Coursera can help you learn linear programming in a way that works best for how you will use it. Several courses help you learn linear programming in the context of financial analysis. Some emphasize mathematics, others concentrate on game theory or computer programming. Some involve spreadsheets, and others call for work with specific programming languages. Courses are at the beginning, intermediate, and advanced levels to accommodate a range of experience. The courses include lectures, readings, and projects so that you can apply what you learn. There are also Guided Projects that let you apply and refine your current knowledge of linear programming.‎

    Online Linear Programming courses offer a convenient and flexible way to enhance your knowledge or learn new Linear Programming skills. Choose from a wide range of Linear Programming courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in Linear 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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