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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

    • J

      Johns Hopkins University

      Foundations of Probability and Random Variables

      Skills you'll gain: R Programming, Statistical Analysis, Statistical Methods, Combinatorics, Data Analysis, Probability, Probability Distribution, Probability & Statistics, Bayesian Statistics, Applied Mathematics, Data Science, Computational Thinking, Artificial Intelligence and Machine Learning (AI/ML), Simulations

      Intermediate · Course · 1 - 3 Months

    • P

      Packt

      The Complete Quantum Computing Course for Beginners

      Skills you'll gain: Object Oriented Programming (OOP), Python Programming, Data Structures, Data Manipulation, Computer Programming, Applied Mathematics, Algorithms, Mathematics and Mathematical Modeling, Data Processing, Scripting, Linear Algebra, Probability, Mathematical Modeling, IBM Cloud, Computer Science, Algebra, Software Installation, Probability & Statistics, Theoretical Computer Science, Artificial Intelligence and Machine Learning (AI/ML)

      4.2
      Rating, 4.2 out of 5 stars
      ·
      29 reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Michigan

      Total Data Quality

      Skills you'll gain: Data Quality, Quantitative Research, Data Validation, Data Integrity, Data Collection, Data Cleansing, Quality Assurance, Data Processing, Data Analysis, Data Access, Statistical Analysis, Sampling (Statistics), Threat Detection, Statistical Methods

      4.6
      Rating, 4.6 out of 5 stars
      ·
      52 reviews

      Beginner · Specialization · 1 - 3 Months

    • C

      Columbia University

      Computational Methods in Pricing and Model Calibration

      Skills you'll gain: Regression Analysis, Derivatives, Financial Market, Statistical Methods, Financial Modeling, Securities (Finance), Mathematical Modeling, Numerical Analysis, Equities, Financial Data, Python Programming, Probability Distribution, Algorithms

      4.4
      Rating, 4.4 out of 5 stars
      ·
      40 reviews

      Intermediate · Course · 1 - 3 Months

    • J

      Johns Hopkins University

      Tidyverse Skills for Data Science in R

      Skills you'll gain: Tidyverse (R Package), Ggplot2, Data Wrangling, Statistical Modeling, Exploratory Data Analysis, Plot (Graphics), R Programming, Data Import/Export, Predictive Modeling, Statistical Visualization, Sampling (Statistics), Data Visualization Software, Statistical Hypothesis Testing, Data Analysis, Data Manipulation, Data Modeling, Web Scraping, Data Integration, Data Cleansing, Data Transformation

      4.5
      Rating, 4.5 out of 5 stars
      ·
      104 reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Colorado Boulder

      Data Science Methods for Quality Improvement

      Skills you'll gain: Process Capability, Statistical Inference, Correlation Analysis, Probability Distribution, Statistical Analysis, Statistical Visualization, Descriptive Statistics, Sampling (Statistics), Statistical Process Controls, Statistics, Data Visualization, Probability & Statistics, Statistical Hypothesis Testing, Data Analysis, Scientific Visualization, Systems Analysis, Data Literacy, Data Analysis Software, R Programming, Quality Control

      Build toward a degree

      4.5
      Rating, 4.5 out of 5 stars
      ·
      49 reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Michigan

      Sampling People, Networks and Records

      Skills you'll gain: Sampling (Statistics), Sample Size Determination, Data Collection, Surveys, Quantitative Research, Statistical Methods, Statistical Software, Probability & Statistics, Probability, Research Methodologies, Network Analysis

      4.3
      Rating, 4.3 out of 5 stars
      ·
      104 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Colorado Boulder

      Stability and Capability in Quality Improvement

      Skills you'll gain: Process Capability, Statistical Process Controls, Statistical Analysis, Data Analysis Software, R Programming, Quality Control, Statistical Methods, Process Analysis, Data Transformation, Statistical Hypothesis Testing, Process Improvement, Probability Distribution

      Build toward a degree

      4
      Rating, 4 out of 5 stars
      ·
      15 reviews

      Intermediate · Course · 1 - 3 Months

    • M

      MathWorks

      Predictive Modeling and Machine Learning with MATLAB

      Skills you'll gain: Supervised Learning, Applied Machine Learning, Matlab, Regression Analysis, Predictive Modeling, Classification And Regression Tree (CART), Machine Learning, Predictive Analytics, Feature Engineering, Statistical Modeling, Data Processing, Sampling (Statistics)

      4.8
      Rating, 4.8 out of 5 stars
      ·
      118 reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Colorado Boulder

      Optical Efficiency and Resolution

      Skills you'll gain: Electrical Engineering, Simulation and Simulation Software, Design Software, Engineering Analysis, Numerical Analysis, System Design and Implementation, Engineering Design Process, Applied Mathematics, Physics, Differential Equations

      4.2
      Rating, 4.2 out of 5 stars
      ·
      62 reviews

      Advanced · Course · 1 - 3 Months

    • Status: Free
      Free
      C

      Carnegie Mellon University

      Statistical Thermodynamics: Molecules to Machines

      Skills you'll gain: Mechanical Engineering, Chemical Engineering, Engineering, Chemical and Biomedical Engineering, Applied Mathematics, Chemistry, Biochemistry, Engineering Analysis, Physics, Molecular, Cellular, and Microbiology, Mathematical Modeling, Physical Science, Probability Distribution

      3.9
      Rating, 3.9 out of 5 stars
      ·
      50 reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Colorado Boulder

      ANOVA and Experimental Design

      Skills you'll gain: Statistical Hypothesis Testing, Statistical Methods, Statistical Analysis, Data Ethics, Statistical Modeling, Data Science, A/B Testing, Data Analysis, Regression Analysis, Probability & Statistics, Sample Size Determination

      Build toward a degree

      3.9
      Rating, 3.9 out of 5 stars
      ·
      18 reviews

      Intermediate · Course · 1 - 4 Weeks

    Discrete Mathematics learners also search

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    1…323334…58

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

    • Foundations of Probability and Random Variables: Johns Hopkins University
    • The Complete Quantum Computing Course for Beginners: Packt
    • Total Data Quality: University of Michigan
    • Computational Methods in Pricing and Model Calibration: Columbia University
    • Tidyverse Skills for Data Science in R: Johns Hopkins University
    • Data Science Methods for Quality Improvement: University of Colorado Boulder
    • Sampling People, Networks and Records: University of Michigan
    • Stability and Capability in Quality Improvement: University of Colorado Boulder
    • Predictive Modeling and Machine Learning with MATLAB: MathWorks
    • Optical Efficiency and Resolution: University of Colorado Boulder

    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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