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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

    • U

      University of Colorado Boulder

      Analytical Mechanics for Spacecraft Dynamics

      Skills you'll gain: Engineering Analysis, Vibrations, Mechanics, Finite Element Methods, Differential Equations, Applied Mathematics, Mathematical Modeling, Linear Algebra, Calculus

      4.8
      Rating, 4.8 out of 5 stars
      ·
      10 reviews

      Advanced · 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

    • É

      École Polytechnique Fédérale de Lausanne

      Functional Program Design in Scala (Scala 2 version)

      Skills you'll gain: Scala Programming, Functional Design, Software Design Patterns, Algorithms, Data Structures, Simulations

      4.6
      Rating, 4.6 out of 5 stars
      ·
      10 reviews

      Intermediate · Course · 1 - 3 Months

    • P

      Packt

      Data Visualization in Stata

      Skills you'll gain: Statistical Visualization, Data Visualization Software, Stata, Scatter Plots, Histogram, Box Plots, Data Presentation, Graphing, Exploratory Data Analysis, Descriptive Statistics, Heat Maps

      Intermediate · Course · 1 - 3 Months

    • K

      Korea Advanced Institute of Science and Technology(KAIST)

      Differential Equations Part III Systems of Equations

      Skills you'll gain: Differential Equations, Applied Mathematics, Advanced Mathematics, Linear Algebra, Calculus, Engineering Analysis, Mathematical Modeling

      4.1
      Rating, 4.1 out of 5 stars
      ·
      11 reviews

      Intermediate · 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

    • U

      University of Colorado Boulder

      Modeling and Predicting Climate Anomalies

      Skills you'll gain: Matplotlib, Dimensionality Reduction, Unsupervised Learning, Machine Learning Algorithms, Applied Machine Learning, Pandas (Python Package), Statistical Analysis, Machine Learning, Regression Analysis, Environmental Policy, Data Science, Data Analysis, Scikit Learn (Machine Learning Library), Supervised Learning, NumPy, Environment, Environmental Issue, International Relations, Policy Analysis, Energy and Utilities

      Intermediate · Specialization · 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

    • S

      Sungkyunkwan University

      Machine Learning Algorithms

      Skills you'll gain: Machine Learning Algorithms, Decision Tree Learning, Unsupervised Learning, Machine Learning, Supervised Learning, Python Programming, Algorithms, Linear Algebra, Bayesian Statistics, Probability & Statistics

      3.5
      Rating, 3.5 out of 5 stars
      ·
      8 reviews

      Mixed · Course · 1 - 4 Weeks

    • C

      Coursera Project Network

      Simulation of Call Centre Operations Using R Simmer

      Skills you'll gain: Simulation and Simulation Software, Resource Management, Resource Allocation, Call Center Experience, Process Management, Data Analysis, Plot (Graphics), R Programming, Statistical Analysis, Operational Analysis, Statistical Modeling

      Beginner · Guided Project · Less Than 2 Hours

    • Status: New
      New
      P

      Packt

      Statistics & Mathematics for Data Science & Data Analytics

      Skills you'll gain: Descriptive Statistics, Statistical Hypothesis Testing, Probability, Probability & Statistics, Statistics, Machine Learning Algorithms, Regression Analysis, Statistical Analysis, Data Analysis, Statistical Methods, Probability Distribution, Random Forest Algorithm, Statistical Inference, Predictive Analytics, Correlation Analysis, Sample Size Determination

      Intermediate · Course · 1 - 3 Months

    • U

      University of Colorado Boulder

      Resampling, Selection and Splines

      Skills you'll gain: Data Science, Statistical Machine Learning, Dimensionality Reduction, Advanced Analytics, Statistical Modeling, Statistical Analysis, Sampling (Statistics), Statistical Methods, Regression Analysis, Statistical Inference, Machine Learning Methods, Predictive Modeling, Probability Distribution, Performance Tuning

      5
      Rating, 5 out of 5 stars
      ·
      8 reviews

      Intermediate · Course · 1 - 3 Months

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

    • Analytical Mechanics for Spacecraft Dynamics: University of Colorado Boulder
    • Defining, Describing, and Visualizing Data: University of Colorado Boulder
    • Functional Program Design in Scala (Scala 2 version): École Polytechnique Fédérale de Lausanne
    • Data Visualization in Stata: Packt
    • Differential Equations Part III Systems of Equations : Korea Advanced Institute of Science and Technology(KAIST)
    • Modeling Data in the Tidyverse: Johns Hopkins University
    • Modeling and Predicting Climate Anomalies: University of Colorado Boulder
    • Launching into Machine Learning em Português Brasileiro: Google Cloud
    • Machine Learning Algorithms: Sungkyunkwan University
    • Simulation of Call Centre Operations Using R Simmer: Coursera Project Network

    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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