Data Analysis and Interpretation Specialization

开始时间: 06/21/2022 持续时间: Approximately 5 months to complete Suggested pace of 3 hours/week

所在平台: Coursera专项课程

课程类别: 计算机科学

大学或机构: CourseraNew

课程主页: https://www.coursera.org/specializations/data-analysis

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课程详情

Learn SAS or Python programming, expand your knowledge of analytical methods and applications, and conduct original research to inform complex decisions. The Data Analysis and Interpretation Specialization takes you from data novice to data expert in just four project-based courses. You will apply basic data science tools, including data management and visualization, modeling, and machine learning using your choice of either SAS or Python, including pandas and Scikit-learn. Throughout the Specialization, you will analyze a research question of your choice and summarize your insights. In the Capstone Project, you will use real data to address an important issue in society, and report your findings in a professional-quality report. You will have the opportunity to work with our industry partners, DRIVENDATA and The Connection. Help DRIVENDATA solve some of the world's biggest social challenges by joining one of their competitions, or help The Connection better understand recidivism risk for people on parole in substance use treatment. Regular feedback from peers will provide you a chance to reshape your question. This Specialization is designed to help you whether you are considering a career in data, work in a context where supervisors are looking to you for data insights, or you just have some burning questions you want to explore. No prior experience is required. By the end you will have mastered statistical methods to conduct original research to inform complex decisions.

数据分析和解释专业化:学习SAS或Python编程,扩展您对分析方法和应用程序的了解,并进行原创研究以为复杂的决策提供依据。 数据分析和解释专业化课程仅针对四个基于项目的课程,使您从数据新手到数据专家。您将通过选择SAS或Python(包括pandas和Scikit-learn)来应用基本数据科学工具,包括数据管理和可视化,建模和机器学习。在整个专业化过程中,您将分析您选择的研究问题并总结您的见解。在Capstone项目中,您将使用真实数据解决社会中的一个重要问题,并以专业质量的报告来报告您的发现。您将有机会与我们的行业合作伙伴DRIVENDATA和The Connection合作。通过参加一项竞赛来帮助DRIVENDATA解决世界上最大的社会挑战,或者帮助The Connection更好地了解假释使用药物治疗者的再犯风险。同行的定期反馈将为您提供一个重塑您问题的机会。该专业旨在帮助您无论是正在考虑从事数据职业,还是在主管希望您寻求数据洞察力的环境中工作,或者您仅想解决一些亟待解决的问题。无需任何经验。到最后,您将掌握统计方法以进行原始研究,从而为复杂的决策提供依据。

课程大纲

Course: 1

Course Link: https://www.coursera.org/learn/data-visualization?specialization=data-analysis

Title:Data Management and Visualization

Description: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.

Course: 2

Course Link: https://www.coursera.org/learn/data-analysis-tools?specialization=data-analysis

Title:Data Analysis Tools

Description: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.

Course: 3

Course Link: https://www.coursera.org/learn/regression-modeling-practice?specialization=data-analysis

Title:Regression Modeling in Practice

Description: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.

Course: 4

Course Link: https://www.coursera.org/learn/machine-learning-data-analysis?specialization=data-analysis

Title:Machine Learning for Data Analysis

Description: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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课程简介

数据分析和解读专项课程系列(Data Analysis and Interpretation Specialization),该系列包括5门子课程,分别是数据管理和可视化,数据分析工具,回归模型,机器学习,毕业项目,感兴趣的同学可以关注:Learn Data Science Fundamentals-Drive real world impact with a four-course introduction to data science.

课程标签

数据分析 数据解释 数据解读 sas Python 数据管理 数据可视化 数据分析和解释 数据管理和可视化 数据分析工具 回归模型 机器学习

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