- Inference
- Statistics
- Data Science
- Probability
- central limit theorem
- continuous random variables
- Bayes' Theorem
- discrete random variables
Data Science Foundations: Statistical Inference 專項課程
Build Your Statistical Skills for Data Science. Master the Statistics Necessary for Data Science
您將學到的內容有
Explain why probability is important to statistics and data science.
See the relationship between conditional and independent events in a statistical experiment.
Calculate the expectation and variance of several random variables and develop some intuition.
Identify characteristics of “good” estimators and be able to compare competing estimators.
您將獲得的技能
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應用的學習項目
Learners will practice new probability skills. including fundamental statistical analysis of data sets, by completing exercises in Jupyter Notebooks. In addition, learners will test their knowledge by completing benchmark quizzes throughout the courses.
Sequence in calculus up through Calculus II (preferably multivariate calculus) and some programming experience in R.
Sequence in calculus up through Calculus II (preferably multivariate calculus) and some programming experience in R.
專項課程的運作方式
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實踐項目
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此專項課程包含 3 門課程
Probability Theory: Foundation for Data Science
Understand the foundations of probability and its relationship to statistics and data science. We’ll learn what it means to calculate a probability, independent and dependent outcomes, and conditional events. We’ll study discrete and continuous random variables and see how this fits with data collection. We’ll end the course with Gaussian (normal) random variables and the Central Limit Theorem and understand its fundamental importance for all of statistics and data science.
Statistical Inference for Estimation in Data Science
This course introduces statistical inference, sampling distributions, and confidence intervals. Students will learn how to define and construct good estimators, method of moments estimation, maximum likelihood estimation, and methods of constructing confidence intervals that will extend to more general settings.
Statistical Inference and Hypothesis Testing in Data Science Applications
This course will focus on theory and implementation of hypothesis testing, especially as it relates to applications in data science. Students will learn to use hypothesis tests to make informed decisions from data. Special attention will be given to the general logic of hypothesis testing, error and error rates, power, simulation, and the correct computation and interpretation of p-values. Attention will also be given to the misuse of testing concepts, especially p-values, and the ethical implications of such misuse.
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科罗拉多大学波德分校
CU-Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies.
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常見問題
退款政策是如何规定的?
我可以只注册一门课程吗?
有助学金吗?
我可以免费学习课程吗?
此课程是 100% 在线学习吗?是否需要现场参加课程?
完成专项课程需要多长时间?
What background knowledge is necessary?
Do I need to take the courses in a specific order?
完成专项课程后我会获得大学学分吗?
What will I be able to do upon completing the Specialization?
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