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Discrete Math

필터링 기준

"discrete math"에 대한 131개의 결과

University of California San Diego
Mathematical Thinking in Computer Science
획득할 기술: Research and Design, Mathematical Theory & Analysis, Mathematics, Theoretical Computer Science, Strategy and Operations, Computer Programming, Logic, Critical Thinking, Leadership and Management, Python Programming, Algorithms, Programming Principles, Problem Solving, Business Analysis, Statistical Programming
4.4
(2.1k개의 검토)
Beginner · Course · 1-3 Months
무료
무료
무료
Imperial College London
Statistical Analysis with R for Public Health
획득할 기술: Analysis, Bayesian Statistics, Business Analysis, Correlation And Dependence, Data Analysis, Econometrics, General Statistics, Machine Learning, Machine Learning Algorithms, Mathematics, Probability & Statistics, Probability Distribution, R Programming, Regression, Statistical Analysis, Statistical Programming, Statistical Tests
4.7
(1.6k개의 검토)
Beginner · Specialization · 3-6 Months
University of California, Santa Cruz
Bayesian Statistics
획득할 기술: Analysis, Bayesian Statistics, Business Analysis, Data Analysis, Econometrics, Estimation, Forecasting, General Statistics, Graph Theory, Inference, Machine Learning, Markov Model, Mathematics, Probability, Probability & Statistics, Probability Distribution, R Programming, Regression, Statistical Analysis, Statistical Machine Learning, Statistical Programming
4.6
(3.2k개의 검토)
Intermediate · Specialization · 3-6 Months
무료
Stanford University
Introduction to Statistics
획득할 기술: Probability, Bayesian Statistics, Regression, Machine Learning, Experiment, Probability & Statistics, Inference, Statistical Tests, Econometrics, General Statistics, Data Visualization, Data Analysis, Statistical Hypothesis Testing, Basic Descriptive Statistics, Probability Distribution, Correlation And Dependence, Plot (Graphics), Markov Model, Hypothesis Testing, Statistical Analysis
4.5
(1.3k개의 검토)
Beginner · Course · 1-3 Months
Imperial College London
Mathematics for Machine Learning: PCA
획득할 기술: Matrices, General Statistics, Computer Programming, Computer Graphics, Machine Learning, Mathematics, Basic Descriptive Statistics, Python Programming, Computer Graphic Techniques, Analysis, Linear Algebra, Probability & Statistics, Data Analysis, Algebra, Probability Distribution, Lambda Calculus, Linearity, Statistical Programming
4.0
(2.8k개의 검토)
Intermediate · Course · 1-4 Weeks
Imperial College London
Mathematics for Machine Learning
획득할 기술: Algebra, Algorithms, Analysis, Artificial Neural Networks, Basic Descriptive Statistics, Calculus, Computer Graphic Techniques, Computer Graphics, Computer Programming, Data Analysis, Deep Learning, Differential Equations, General Statistics, Linear Algebra, Machine Learning, Machine Learning Algorithms, Mathematical Optimization, Mathematical Theory & Analysis, Mathematics, Matrices, Probability & Statistics, Probability Distribution, Python Programming, Regression, Statistical Programming, Theoretical Computer Science
4.6
(12.9k개의 검토)
Beginner · Specialization · 3-6 Months
무료
MathWorks
Practical Data Science with MATLAB
획득할 기술: Algebra, Analysis, Applied Machine Learning, Business Analysis, Correlation And Dependence, Data Analysis, Data Analysis Software, Data Management, Data Visualization, Econometrics, Exploratory Data Analysis, Extract, Transform, Load, Feature Engineering, General Statistics, Linear Algebra, Machine Learning, Machine Learning Algorithms, Mathematics, Matlab, Plot (Graphics), Predictive Modelling, Probability & Statistics, Probability Distribution, Regression, Statistical Analysis, Statistical Visualization, Web Development
4.7
(928개의 검토)
Beginner · Specialization · 3-6 Months

discrete math과(와) 관련된 검색

discrete mathematics

离散数学概论 discrete mathematics generality

요약하자면, 여기에 가장 인기 있는 discrete math 강좌 10개가 있습니다.

Mathematical Thinking in Computer Science: University of California San Diego
Discrete Mathematics: Shanghai Jiao Tong University
离散数学概论 Discrete Mathematics Generality: Peking University
Basic Modeling for Discrete Optimization: The University of Melbourne
Statistical Analysis with R for Public Health: Imperial College London
Bayesian Statistics: University of California, Santa Cruz
Introduction to Statistics: Stanford University
Mathematics for Machine Learning: PCA: Imperial College London
Mathematics for Computer Science: University of London
Mathematics for Machine Learning: Imperial College London