耶鲁大学统计与数据科学硕士+ 查看更多
耶鲁大学
统计与数据科学硕士
+ 查看更多
- 该项目提供广泛的培训计划,包括统计理论的主要领域(with emphasis on foundations, Bayes theory, decision theory, nonparametric statistics), probability theory, stochastic processes, asymptotics, information theory, machine learning, data analysis, statistical computing, and graphical methods
- 该项目的毕业生在商业界和政府中找到了非常出色的职位。官网可查询往届毕业生就业列表
项目时长:2年全日制
项目授课地点:美国 康涅狄格州 纽黑文
申请要求
申请流程
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学校要求8 门统计学硕士课程和12 门统计与数据科学硕士课程。
Introduction to Statistics
Foreign Assistance to Sub-Saharan Africa: Archival Data Analysis
Data Science Ethics
YData: Data Science for Political Campaigns
Data Exploration and Analysis
(Bayesian) Probability and Statistics
Probability for Data Science
Probability Theory with Applications
Introductory Machine Learning
Linear Models
Intermediate Machine Learning
Advanced Probability
Statistical Inference
Statistical Case Studies
Senior Project
Numerical Linear Algebra: Detenninistic and randomized algorithms
Statistical Case Studies
Computation and Optimization
Statistical Computing
Computational Mathematics for Data Science
Indep Study
Practical Work
Statistical Consulting
Independent Study or Topics Course
Departmental Seminar
Introductory Statistics
YData
YData: Measuring Culture
Intensive Introductory Statistics and Data Science
Data Exploration and Analysis
Theory of Statistics
Computational Tools for Data Science
Stochastic Processes
Biomedical Data Science, Mining and Modeling
Data Analysis
Multivariate Statistics for Social Sciences
Infbnnation Theory
Statistical Case Studies
Senior Project
Topics in Deep Learning: Methods and Biomedical Applications
Applied Machine Learning and Causal Inference Research Seminar
Advanced Optimization Techniques
Applied Spatial Statistics
Statistical Inference on Graphs
Foundations of Reinforcement Learning
Statistics and Data Science Computing Laboratory (1/2 credit)
YData: Text Data Science: An Introduction
YData: Analysis of Baseball Data
YData: Statistics in the Media
YData: COVID-19 Behavior
Theory of Probability and Statistics
Applied Machine Learning and Causal Inference
Design and Analysis of Algorithms
Optimization Techniques
Senior Seminar and Project
Research Design and Causal Inference
Applied Linear Models
Intensive Algorithms
Selected Topics in Statistical Decision Theory
Introduction to Random Matrix Theory and Applications
Statistical Methods in Human Genetics
Spectral Graph Theory
Probabilistic Networks, Algorithms, and Applications
Nonparametric Estimation and Machine Learning
Topics on Random Graphs
Infbnnation Theory Tools in Probability and Statistics
Topological Data Analysis
Signal Processing for Data Science
Function Estimation
High-Dimensional Function Estimation (prev title)
Statistical Methods in Neuroimaging
Research Seminar in Probability
Placeholder — Monograph
Foreign Assistance to Sub-Saharan Africa: Archival Data Analysis
Data Science Ethics
YData: Data Science for Political Campaigns
Data Exploration and Analysis
(Bayesian) Probability and Statistics
Probability for Data Science
Probability Theory with Applications
Introductory Machine Learning
Linear Models
Intermediate Machine Learning
Advanced Probability
Statistical Inference
Statistical Case Studies
Senior Project
Numerical Linear Algebra: Detenninistic and randomized algorithms
Statistical Case Studies
Computation and Optimization
Statistical Computing
Computational Mathematics for Data Science
Indep Study
Practical Work
Statistical Consulting
Independent Study or Topics Course
Departmental Seminar
Introductory Statistics
YData
YData: Measuring Culture
Intensive Introductory Statistics and Data Science
Data Exploration and Analysis
Theory of Statistics
Computational Tools for Data Science
Stochastic Processes
Biomedical Data Science, Mining and Modeling
Data Analysis
Multivariate Statistics for Social Sciences
Infbnnation Theory
Statistical Case Studies
Senior Project
Topics in Deep Learning: Methods and Biomedical Applications
Applied Machine Learning and Causal Inference Research Seminar
Advanced Optimization Techniques
Applied Spatial Statistics
Statistical Inference on Graphs
Foundations of Reinforcement Learning
Statistics and Data Science Computing Laboratory (1/2 credit)
YData: Text Data Science: An Introduction
YData: Analysis of Baseball Data
YData: Statistics in the Media
YData: COVID-19 Behavior
Theory of Probability and Statistics
Applied Machine Learning and Causal Inference
Design and Analysis of Algorithms
Optimization Techniques
Senior Seminar and Project
Research Design and Causal Inference
Applied Linear Models
Intensive Algorithms
Selected Topics in Statistical Decision Theory
Introduction to Random Matrix Theory and Applications
Statistical Methods in Human Genetics
Spectral Graph Theory
Probabilistic Networks, Algorithms, and Applications
Nonparametric Estimation and Machine Learning
Topics on Random Graphs
Infbnnation Theory Tools in Probability and Statistics
Topological Data Analysis
Signal Processing for Data Science
Function Estimation
High-Dimensional Function Estimation (prev title)
Statistical Methods in Neuroimaging
Research Seminar in Probability
Placeholder — Monograph
*以上列表仅代表部分课程仅供参考
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