Skills you'll gain: Mathematics, Graph Theory, Computer Science, Computer Programming, Python Programming, Statistical Programming, Data Science, Algebra, Theoretical Computer Science, Probability & Statistics, Algorithms, Calculus, Combinatorics, Data Analysis, Statistical Analysis, General Statistics, Mathematical Theory & Analysis, Programming Principles, Bayesian Statistics, Computational Thinking, Geometry, Applied Mathematics, Correlation And Dependence, Estimation, Probability Distribution, Computational Logic, Business Analysis, Communication, Computer Architecture, Critical Thinking, Cryptography, Data Visualization, Entrepreneurship, Leadership and Management, Machine Learning, Markov Model, Microarchitecture, Problem Solving, Research and Design, Scientific Visualization, Security Engineering, Statistical Visualization, Strategy and Operations
Beginner · Specialization · 3-6 Months
Skills you'll gain: Mathematics, Algebra, Linear Algebra, Mathematical Theory & Analysis, Algorithms, Calculus, Machine Learning, Theoretical Computer Science, Artificial Neural Networks, Deep Learning, Machine Learning Algorithms, Probability & Statistics, Regression, Computer Programming, Differential Equations, Econometrics, General Statistics, Python Programming, Statistical Machine Learning, Statistical Programming, Statistical Analysis
Beginner · Specialization · 1-3 Months
Skills you'll gain: Data Science, General Statistics, Probability & Statistics, Statistical Tests, Estimation, Basic Descriptive Statistics, Correlation And Dependence, Probability Distribution, Regression, Bayesian Statistics, Data Analysis, Data Visualization, Econometrics, Experiment, Machine Learning, Markov Model, Plot (Graphics), Statistical Analysis, Statistical Visualization
Beginner · Course · 1-3 Months
Skills you'll gain: Mathematics, Algebra, Linear Algebra, Machine Learning, Computer Programming, General Statistics, Probability & Statistics, Python Programming, Statistical Programming, Dimensionality Reduction, Basic Descriptive Statistics, Data Analysis, Probability Distribution, Regression, Computer Graphic Techniques, Computer Graphics, Experiment, Mathematical Theory & Analysis
Intermediate · Course · 1-4 Weeks
Earn a degree
Degree · 1-4 Years
Skills you'll gain: Mathematics, Algebra, Geometry, Algorithms, Applied Mathematics, Computational Thinking, Theoretical Computer Science, Computational Logic, Business Analysis, Computer Programming, Critical Thinking, Leadership and Management, Mathematical Theory & Analysis, Problem Solving, Programming Principles, Python Programming, Research and Design, Statistical Programming, Strategy and Operations
Beginner · Course · 1-3 Months
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.