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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/data-science-with-r-capstone-project
课程评论：没有评论
课程名称：数据科学与R - 顶点项目 课程概述： 在这个顶点课程中，学员将运用在IBM数据科学与R专业课程或IBM数据分析与Excel及R专业证书中所学的各种数据科学技能和技术。学员将担任一名刚加入组织的数据科学家，面临一个需要进行数据收集、分析、基本假设检验、可视化和建模的真实世界数据集的挑战。课程将涵盖数据的多源收集与理解、利用Tidyverse进行数据整理与准备、使用SQL、Tidyverse和ggplot2进行探索性数据分析、进行线性回归建模、创建图表与视觉展示数据，并建立交互式仪表盘。 最终，学员将呈现数据分析报告，并为组织内的各种利益相关者提供执行摘要。 课程大纲： 1. 模块1 - 顶点项目概述与数据收集 2. 模块2 - 数据整理 3. 模块3 - 使用SQL、Tidyverse和ggplot2进行探索性数据分析（在这一阶段，学员将运用数据收集与整理的知识，学习SQL查询和可视化，并进行实践，完成三个实验室任务） 4. 模块4 - 预测分析 5. 模块5 - 构建R Shiny仪表盘应用 6. 模块6 - 展示您的数据驱动洞察 通过这一课程，学员将深化对数据科学流程的理解，提升使用R进行数据分析的能力，并为未来的职业发展打下坚实基础。
Name:Module 1 - Capstone Overview and Data Collection
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Name:Module 2 - Data Wrangling
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Name:Module 3: Performing Exploratory Data Analysis with SQL, Tidyverse & ggplot2
Description:At this stage of the Capstone Project, you have gained some valuable working knowledge of data collection and data wrangling. You have also learned a lot about SQL querying and visualization. Congratulations! Now it's time to apply some of your new knowledge and learn about Exploratory Data Analysis (EDA) techniques, again through practice. You can use the datasets you wrangled in the previous Module. However, if you had any issues completing the wrangling, no worries - we have prepared some clean datasets for you to use. You will be asked to complete three labs:
Name:Module 4: Predictive Analysis
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Name:Module 5 - Building a R Shiny Dashboard App
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Name:Module 6 - Present Your Data-Driven Insights
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In this capstone course, you will apply various data science skills and techniques that you have learned as part of the previous courses in the IBM Data Science with R Specialization or IBM Data Analytics with Excel and R Professional Certificate. For this project, you will assume the role of a Data Scientist who has recently joined an organization and be presented with a challenge that requires data collection, analysis, basic hypothesis testing, visualization, and modeling to be performed on real-world datasets. You will collect and understand data from multiple sources, conduct data wrangling and preparation with Tidyverse, perform exploratory data analysis with SQL, Tidyverse and ggplot2, model data with linear regression, create charts and plots to visualize the data, and build an interactive dashboard. The project will culminate with a presentation of your data analysis report, with an executive summary for the various stakeholders in the organization.
