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  • Discrete Mathematics

Results for "discrete mathematics"


  • T

    The Hong Kong University of Science and Technology

    Discrete Mathematical Tools for Computer Science

    Skills you'll gain: Probability, Computational Logic, Combinatorics, Bayesian Statistics, Algorithms, Theoretical Computer Science, Mathematical Software, Mathematical Theory & Analysis, Cryptography, Logical Reasoning, Deductive Reasoning, Computational Thinking, Computer Science, Encryption, Data Structures, Arithmetic, General Mathematics, Public Key Cryptography Standards (PKCS), Problem Solving, Cybersecurity

    Beginner · Specialization · 3 - 6 Months

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • U

    University of California San Diego

    Introduction to Discrete Mathematics for Computer Science

    Skills you'll gain: Graph Theory, Logical Reasoning, Cryptographic Protocols, Combinatorics, Computational Logic, Deductive Reasoning, Graphing, Cryptography, Probability, Key Management, Computational Thinking, Encryption, Probability Distribution, Network Analysis, Theoretical Computer Science, Bayesian Statistics, Python Programming, Cybersecurity, Algorithms, Arithmetic

    ★ 4.5 (3.7K) · Beginner · Specialization · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • B

    Birla Institute of Technology & Science, Pilani

    Discrete Mathematics for Computer Science and Engineering

    Skills you'll gain: Theoretical Computer Science, Mathematics and Mathematical Modeling, Applied Mathematics, Algorithms, Cryptography, Data Management

    Beginner · Course · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: Build toward a degree
    Build toward a degree
  • S

    Shanghai Jiao Tong University

    Discrete Mathematics

    Skills you'll gain: Combinatorics, Graph Theory, Theoretical Computer Science, Network Model, Mathematical Theory & Analysis, Advanced Mathematics, Network Analysis, Mathematics and Mathematical Modeling, Logical Reasoning, General Mathematics, Algorithms, Probability, Computer Science

    ★ 3.3 (203) · Intermediate · Course · 1 - 3 Months

    Category: Preview
    Preview
    Category: Credit offered
    Credit offered
  • B

    Birla Institute of Technology & Science, Pilani

    Mathematics for Engineering

    Skills you'll gain: Data Analysis, Computational Logic, Integral Calculus, Trigonometry, Linear Algebra, Engineering Analysis, Logical Reasoning, Deductive Reasoning, Probability & Statistics, Statistical Analysis, Calculus, Statistical Methods, Analysis, Advanced Mathematics, Bayesian Statistics, Statistical Inference, Theoretical Computer Science, Mathematics and Mathematical Modeling, Numerical Analysis, Descriptive Analytics

    ★ 4.5 (196) · Beginner · Specialization · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • U

    University of London

    Essential Mathematics for Computer Science

    Skills you'll gain: Computational Logic, Algorithms, Arithmetic, Applied Mathematics, Advanced Mathematics, Mathematics and Mathematical Modeling, Deductive Reasoning, Mathematical Theory & Analysis, Trigonometry, Geometry, Statistics, General Mathematics, Graphing, Computer Science, Mathematical Modeling, Programming Principles, Business Mathematics, Business Logic, Algebra, Problem Solving

    Beginner · Specialization · 3 - 6 Months

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Build toward a degree
    Build toward a degree

What brings you to Coursera today?

  • J

    Johns Hopkins University

    Linear Algebra from Elementary to Advanced

    Skills you'll gain: Linear Algebra, Algebra, Applied Mathematics, Advanced Mathematics, Artificial Intelligence and Machine Learning (AI/ML), Mathematical Modeling, Engineering Analysis, Mathematical Theory & Analysis, Numerical Analysis, Geometry, Applied Machine Learning, Markov Model

    ★ 4.7 (229) · Beginner · Specialization · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • I

    Imperial College London

    Mathematics for Machine Learning

    Skills you'll gain: Dimensionality Reduction, Linear Algebra, Regression Analysis, NumPy, Calculus, Data Preprocessing, Unsupervised Learning, Feature Engineering, Applied Mathematics, Model Optimization, Mathematical Software, Jupyter, Statistics, Numerical Analysis, Applied Machine Learning, Artificial Neural Networks, Data Science, Data Manipulation, Python Programming, Data Transformation

    ★ 4.6 (15K) · Beginner · Specialization · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • T

    The Hong Kong University of Science and Technology

    Discrete Math for Computer Science - Logic & Set Theory

    Skills you'll gain: Computational Logic, Logical Reasoning, Theoretical Computer Science, Deductive Reasoning, Programming Principles, Mathematics and Mathematical Modeling, Computer Science, Algorithms

    Beginner · Course · 1 - 3 Months

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • T

    The Hong Kong University of Science and Technology

    Mathematics for Engineers

    Skills you'll gain: Differential Equations, Linear Algebra, Matlab, Engineering Analysis, Numerical Analysis, Integral Calculus, Mathematical Software, Mechanical Engineering, Calculus, Engineering Calculations, electromagnetics, Algebra, Applied Mathematics, Mathematical Modeling, Engineering, Advanced Mathematics, Geometry, Computational Thinking, Simulation and Simulation Software, Mechanics

    ★ 4.8 (7.8K) · Beginner · Specialization · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • U

    Universitat Politècnica de València

    Basic Math: Algebra

    Skills you'll gain: Linear Algebra, Algebra, Geometry, General Mathematics, Applied Mathematics, Arithmetic

    Beginner · Course · 1 - 4 Weeks

    Category: New
    New
    Category: Preview
    Preview
    Category: Credit offered
    Credit offered
  • T

    The Hong Kong University of Science and Technology

    Discrete Math for Computer Science - Counting & Probability

    Skills you'll gain: Bayesian Statistics

    Beginner · Course · 1 - 3 Months

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
1234…70

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

  • Discrete Mathematical Tools for Computer Science: The Hong Kong University of Science and Technology
  • Introduction to Discrete Mathematics for Computer Science: University of California San Diego
  • Discrete Mathematics for Computer Science and Engineering: Birla Institute of Technology & Science, Pilani
  • Discrete Mathematics: Shanghai Jiao Tong University
  • Mathematics for Engineering: Birla Institute of Technology & Science, Pilani
  • Essential Mathematics for Computer Science: University of London
  • Linear Algebra from Elementary to Advanced: Johns Hopkins University
  • Mathematics for Machine Learning: Imperial College London
  • Discrete Math for Computer Science - Logic & Set Theory: The Hong Kong University of Science and Technology
  • Mathematics for Engineers: The Hong Kong University of Science and Technology

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 is a branch of mathematics that deals with discrete elements that use algebra and arithmetic. It encompasses a variety of topics such as logic, set theory, graph theory, and combinatorics. Discrete mathematics is crucial because it provides the foundational concepts necessary for computer science, cryptography, and algorithm design. Understanding these principles helps in developing efficient algorithms and data structures, which are essential in programming and software development.‎

A background in discrete mathematics can lead to various career opportunities. Positions such as data analyst, software developer, systems analyst, and operations researcher often require knowledge of discrete mathematics. Additionally, roles in academia and research, particularly in fields like computer science and engineering, value this expertise. As technology continues to advance, the demand for professionals skilled in discrete mathematics is likely to grow.‎

To learn discrete mathematics effectively, you should focus on several key skills. These include logical reasoning, problem-solving, and analytical thinking. Familiarity with mathematical proofs and the ability to work with algorithms and data structures are also important. Additionally, programming skills can enhance your understanding of how discrete mathematics applies in real-world scenarios, particularly in computer science.‎

There are several excellent online courses available for studying discrete mathematics. Notable options include the Discrete Mathematics course, which covers essential topics and applications. The Introduction to Discrete Mathematics for Computer Science Specialization is another comprehensive choice, providing a deeper dive into the subject tailored for aspiring computer scientists.‎

Yes. You can start learning discrete mathematics on Coursera for free in two ways:

  1. Preview the first module of many discrete mathematics courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

If you want to keep learning, earn a certificate in discrete mathematics, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

To learn discrete mathematics, start by identifying your learning goals and preferred study methods. You can enroll in online courses, such as the Discrete Mathematics for Computer Science and Engineering course, which provides structured content. Supplement your learning with textbooks, practice problems, and online forums to discuss concepts with peers. Consistent practice and application of concepts will reinforce your understanding.‎

Typical topics covered in discrete mathematics courses include logic, set theory, functions, relations, combinatorics, graph theory, and algorithms. These subjects form the backbone of many computer science applications, enabling learners to understand complex systems and solve problems effectively. Courses often emphasize both theoretical concepts and practical applications, ensuring a well-rounded understanding.‎

For training and upskilling employees, courses like the Introduction to Discrete Mathematics for Computer Science Specialization are highly beneficial. They provide a comprehensive overview of discrete mathematics tailored for professionals in tech and engineering fields. Such courses can enhance problem-solving skills and analytical thinking, making them valuable for workforce development. ‎

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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