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    • Discrete Mathematics

    Discrete Mathematics Courses Online

    Master discrete mathematics for computer science and engineering. Learn about logic, set theory, combinatorics, graph theory, and algorithms.

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    Explore the Discrete Mathematics Course Catalog

    • R

      Rice University

      Physics of Light and Materials

      Skills you'll gain: Physics, Mechanics, Physical Science, Trigonometry, Mathematical Modeling, Advanced Mathematics, Linear Algebra, Differential Equations, Applied Mathematics, Integral Calculus

      4.9
      Rating, 4.9 out of 5 stars
      ·
      7 reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of Colorado Boulder

      Defining, Describing, and Visualizing Data

      Skills you'll gain: Data-Driven Decision-Making, Descriptive Statistics, Data Analysis, Probability Distribution, Statistical Software, Statistics, Statistical Visualization, Data Visualization, Statistical Analysis, Box Plots, Probability, R Programming, Probability & Statistics, Data Manipulation, Histogram, Taxonomy

      4.5
      Rating, 4.5 out of 5 stars
      ·
      10 reviews

      Beginner · Course · 1 - 3 Months

    • J

      Johns Hopkins University

      Modeling Data in the Tidyverse

      Skills you'll gain: Statistical Modeling, Exploratory Data Analysis, R Programming, Predictive Modeling, Sampling (Statistics), Statistical Hypothesis Testing, Tidyverse (R Package), Data Analysis, Data Modeling, Regression Analysis, Data Science, Classification And Regression Tree (CART), Statistical Inference, Predictive Analytics, Statistical Analysis, Rmarkdown, Probability & Statistics, Machine Learning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      9 reviews

      Mixed · Course · 1 - 3 Months

    • G

      Google Cloud

      Launching into Machine Learning em Português Brasileiro

      Skills you'll gain: Exploratory Data Analysis, Data Quality, Applied Machine Learning, Data Cleansing, Machine Learning, MLOps (Machine Learning Operations), Machine Learning Algorithms, Supervised Learning, Google Cloud Platform, Data Processing, Data Analysis, Predictive Modeling, Big Data, Statistical Analysis, Sampling (Statistics), Regression Analysis, Performance Tuning

      4.6
      Rating, 4.6 out of 5 stars
      ·
      32 reviews

      Beginner · Course · 1 - 3 Months

    • Status: New
      New
      N

      Northeastern University

      Generative AI: Foundations and Concepts

      Skills you'll gain: Generative AI, Artificial Neural Networks, Deep Learning, Bayesian Network, Machine Learning Methods, Artificial Intelligence and Machine Learning (AI/ML), Mathematical Modeling, Computer Vision, Applied Mathematics, Machine Learning, Network Architecture, Probability & Statistics

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Launching into Machine Learning en Français

      Skills you'll gain: Exploratory Data Analysis, Data Analysis, Applied Machine Learning, Data Quality, Data Cleansing, Machine Learning, Supervised Learning, Google Cloud Platform, Regression Analysis, Sampling (Statistics), Performance Tuning

      4.5
      Rating, 4.5 out of 5 stars
      ·
      11 reviews

      Beginner · Course · 1 - 3 Months

    • Status: New
      New
      J

      Johns Hopkins University

      Introduction to Neural Networks

      Skills you'll gain: Artificial Neural Networks, Machine Learning Algorithms, Deep Learning, Computer Vision, Image Analysis, Machine Learning, Linear Algebra, Artificial Intelligence, Performance Tuning, Probability & Statistics

      Intermediate · Course · 1 - 3 Months

    • R

      Rice University

      Physics of Geometrical and Physical Optics

      Skills you'll gain: Physics, Engineering Calculations, Applied Mathematics, Advanced Mathematics, Physical Science, Mathematical Modeling, Trigonometry, Calculus, Linear Algebra

      4.8
      Rating, 4.8 out of 5 stars
      ·
      6 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free
      Free
      U

      University of Leeds

      Statistical Methods

      Skills you'll gain: Exploratory Data Analysis, Statistical Methods, Statistical Modeling, Data Collection, Statistics, Statistical Inference, R Programming, Probability, Data Analysis, Probability Distribution, Simulations, Statistical Visualization, Descriptive Statistics

      4.8
      Rating, 4.8 out of 5 stars
      ·
      9 reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of Michigan

      Measuring Total Data Quality

      Skills you'll gain: Data Quality, Quantitative Research, Data Validation, Data Collection, Data Processing, Data Analysis, Data Access, Statistical Analysis, Sampling (Statistics)

      4.5
      Rating, 4.5 out of 5 stars
      ·
      6 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free
      Free
      D

      Duke University

      Inferenzstatistik

      Skills you'll gain: Statistical Inference, Statistical Hypothesis Testing, Statistical Reporting, Statistical Analysis, Data Analysis, Probability & Statistics, Statistical Methods, Data Analysis Software, Statistical Software, R Programming, Sampling (Statistics), Probability Distribution, Software Installation

      Beginner · Course · 1 - 3 Months

    • Status: Free
      Free
      B

      Ball State University

      Introduction to Data Science

      Skills you'll gain: Data Ethics, Data Collection, Probability & Statistics, Statistics, Data Visualization Software, R Programming, Data Science, Sampling (Statistics), Probability, Simulations, Data Wrangling, Analytical Skills, Data Analysis, Mathematical Theory & Analysis, General Mathematics, Statistical Analysis, Information Privacy, Regression Analysis, Arithmetic, Data Structures

      Build toward a degree

      Beginner · Course · 1 - 3 Months

    Discrete Mathematics learners also search

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    1…515253…59

    In summary, here are 10 of our most popular discrete mathematics courses

    • Physics of Light and Materials: Rice University
    • Defining, Describing, and Visualizing Data: University of Colorado Boulder
    • Modeling Data in the Tidyverse: Johns Hopkins University
    • Launching into Machine Learning em Português Brasileiro: Google Cloud
    • Generative AI: Foundations and Concepts: Northeastern University
    • Launching into Machine Learning en Français: Google Cloud
    • Introduction to Neural Networks: Johns Hopkins University
    • Physics of Geometrical and Physical Optics: Rice University
    • Statistical Methods: University of Leeds
    • Measuring Total Data Quality: University of Michigan

    Skills you can learn in Probability And Statistics

    R Programming (19)
    Inference (16)
    Linear Regression (12)
    Statistical Analysis (12)
    Statistical Inference (11)
    Regression Analysis (10)
    Biostatistics (9)
    Bayesian (7)
    Logistic Regression (7)
    Probability Distribution (7)
    Bayesian Statistics (6)
    Medical Statistics (6)

    Frequently Asked Questions about Discrete Mathematics

    Discrete mathematics refers to a group of mathematics branches that deal with discrete objects instead of continuous objects. In discrete mathematics, objects have distinct, separate values represented by integers, unlike real numbers used in continuous mathematics. Discrete mathematics includes combinatorics, set theory, graph theory, number theory, and probability. It is integral to computer science and plays a role in the field of data science.‎

    You may consider learning discrete mathematics if you want to study computer science or work in a data science field. Discrete mathematics is a foundation of computer science, and programmers often use principles of set theory, probability, and combinations to analyze algorithms when writing programs and applications. Learning discrete mathematics can also help boost other useful skills like logic, reasoning, and problem-solving, making you a more marketable job candidate. ‎

    Typical careers that use discrete mathematics are in the computer science field, such as software development, programming, and cryptography. Data scientists and data analysts may use their knowledge of discrete mathematics in their work. Other careers that can incorporate discrete mathematics include electrical and mechanical engineers in addition to data analysts, business analysts, and market researchers. Discrete mathematics also influences the work of urban planners, epidemiologists, and social scientists who collect and analyze large amounts of data.‎

    Online courses can introduce you to core concepts of discrete mathematics, such as sets, relations, and functions. Lessons include topics like partial orders, enumerative combinatorics, and the binomial coefficient, and you have opportunities to apply the concepts to real-world applications. You may choose courses that cover specific subjects like graph theory or probability to increase your knowledge of these disciplines. Alternatively, you may decide to take courses that explore the application of discrete mathematics in specific fields like data science, computer science, or machine learning.‎

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

    When looking to enhance your workforce's skills in Discrete Math, 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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