- Statistics
- Data Analysis
- Machine Learning
- Regression Analysis
- SAS Language
- Python Programming
- Data Management
- Chi-Squared (Chi-2) Distribution
- Statistical Hypothesis Testing
- Analysis Of Variance (ANOVA)
- Logistic Regression
- Exploratory Data Analysis
数据分析和解释 专项课程
Learn Data Science Fundamentals. Drive real world impact with a four-course introduction to data science.
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您将获得的技能
关于此 专项课程
无需相关领域的预备知识无需相关经验。
无需相关领域的预备知识无需相关经验。
专项课程的运作方式
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此专项课程包含 5 门课程
数据管理与可视化
Whether being used to customize advertising to millions of website visitors or streamline inventory ordering at a small restaurant, data is becoming more integral to success. Too often, we’re not sure how use data to find answers to the questions that will make us more successful in what we do. In this course, you will discover what data is and think about what questions you have that can be answered by the data – even if you’ve never thought about data before. Based on existing data, you will learn to develop a research question, describe the variables and their relationships, calculate basic statistics, and present your results clearly. By the end of the course, you will be able to use powerful data analysis tools – either SAS or Python – to manage and visualize your data, including how to deal with missing data, variable groups, and graphs. Throughout the course, you will share your progress with others to gain valuable feedback, while also learning how your peers use data to answer their own questions.
数据分析工具
In this course, you will develop and test hypotheses about your data. You will learn a variety of statistical tests, as well as strategies to know how to apply the appropriate one to your specific data and question. Using your choice of two powerful statistical software packages (SAS or Python), you will explore ANOVA, Chi-Square, and Pearson correlation analysis. This course will guide you through basic statistical principles to give you the tools to answer questions you have developed. Throughout the course, you will share your progress with others to gain valuable feedback and provide insight to other learners about their work.
回归建模实践
This course focuses on one of the most important tools in your data analysis arsenal: regression analysis. Using either SAS or Python, you will begin with linear regression and then learn how to adapt when two variables do not present a clear linear relationship. You will examine multiple predictors of your outcome and be able to identify confounding variables, which can tell a more compelling story about your results. You will learn the assumptions underlying regression analysis, how to interpret regression coefficients, and how to use regression diagnostic plots and other tools to evaluate the quality of your regression model. Throughout the course, you will share with others the regression models you have developed and the stories they tell you.
使用机器学习进行数据分析
Are you interested in predicting future outcomes using your data? This course helps you do just that! Machine learning is the process of developing, testing, and applying predictive algorithms to achieve this goal. Make sure to familiarize yourself with course 3 of this specialization before diving into these machine learning concepts. Building on Course 3, which introduces students to integral supervised machine learning concepts, this course will provide an overview of many additional concepts, techniques, and algorithms in machine learning, from basic classification to decision trees and clustering. By completing this course, you will learn how to apply, test, and interpret machine learning algorithms as alternative methods for addressing your research questions.
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卫斯连大学
Wesleyan University, founded in 1831, is a diverse, energetic liberal arts community where critical thinking and practical idealism go hand in hand. With our distinctive scholar-teacher culture, creative programming, and commitment to interdisciplinary learning, Wesleyan challenges students to explore new ideas and change the world. Our graduates go on to lead and innovate in a wide variety of industries, including government, business, entertainment, and science.


常见问题
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完成专项课程后我会获得大学学分吗?
Can I take the Specialization for free?
How long does it take to complete the Data Analysis and Interpretation Specialization?
此专项课程中每门课程的开课频率为多久?
Do I need to take the courses in a specific order?
Will I earn university credit for completing the Data Analysis and Interpretation Specialization?
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What software will I need to complete the assignments?
What background knowledge is necessary?
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