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所在平台: Udemy |
课程主页: https://www.udemy.com/course/certification-in-data-visualization-and-storytelling/
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课程名称：数据可视化与故事讲述认证 课程概述： 该课程是为数据可视化和故事讲述专业人士设计的，适合初学者、经验丰富的数据分析师、数据科学家以及对数据驱动叙事有兴趣的讲故事者。课程旨在提升学员的数据处理和叙述能力，助力职业发展，并在数据可视化与故事讲述领域中产生积极的影响。 学习内容包括： - 掌握数据可视化和故事讲述所需的基本技能与功能。 - 转化对数据可视化应用、技术、数据表示、特征工程、数据分析、预处理及故事讲述技巧的了解。 - 获取推荐的模板和格式，以便处理数据可视化与故事讲述的相关事项。 - 学习实用案例，了解国际货币基金组织及其货币政策和财政政策如何影响数据可视化的发展，并应用相关框架和格式。 课程框架： 通过生动的视频讲座、案例研究、评估、可下载资源及互动练习，探索数据可视化与故事讲述领域，涵盖数据表示、特征工程、数据可视化技术、交互式仪表板、视觉分析、数据预处理、数据分析、数据驱动叙事等多个章节。还将探讨印度社会文化环境中使用数据可视化技术的情感分析、舆情挖掘与互动可视化等内容，并进行数据可视化相关的洞见与未来趋势分析，最终完成一个数据可视化的综合项目。 课程内容包括： 1. 数据可视化简介 2. 数据类型及可视化技术 3. 数据准备与清洗 4. 探索性数据分析 (EDA) 5. 高级数据可视化技术 6. 不确定性与预测的可视化 7. 数据叙事 8. 设计原则与美学 9. 伦理与负责任的数据可视化 10. 数据可视化工具与技术 11. 综合项目 通过该课程，学员将会获得丰富的全球数据可视化项目经验，以及相关的模板、工作表、阅读材料、测验及自我评估工具，以全面提升他们在数据可视化与故事讲述方面的知识与技能。
DescriptionTake the next step in your career as data visualization and storytelling professionals! Whether you're an up-and-coming data visualization specialist, an experienced data analyst, aspiring data scientist specializing in visualization, or budding storyteller in data-driven narratives, this course is an opportunity to sharpen your data processing and storytelling capabilities, increase your efficiency for professional growth, and make a positive and lasting impact in the field of data visualization and storytelling.With this course as your guide, you learn how to:● All the fundamental functions and skills required for data visualization and storytelling.● Transform knowledge of data visualization applications and techniques, data representation and feature engineering, data analysis and preprocessing, and storytelling techniques.● Get access to recommended templates and formats for details related to data visualization and storytelling techniques.● Learn from informative case studies, gaining insights into data visualization and storytelling techniques for various scenarios. Understand how the International Monetary Fund, monetary policy, and fiscal policy impact advancements in data visualization, with practical forms and frameworks.● Learn from informative case studies, gaining insights into data visualization and storytelling techniques for various scenarios. Understand how the International Monetary Fund, monetary policy, and fiscal policy impact advancements in data visualization, with practical formats and frameworks.The Frameworks of the CourseEngaging video lectures, case studies, assessments, downloadable resources, and interactive exercises. This course is designed to explore the field of data visualization and storytelling, covering various chapters and units. You'll delve into data representation, feature engineering, data visualization techniques, interactive dashboards, visual analytics, data preprocessing, data analysis, data-driven storytelling, dashboard design, advanced topics in data visualization, and future trends.The socio-cultural environment module using data visualization techniques delves into sentiment analysis and opinion mining, data-driven storytelling, and interactive visualization in the context of India's socio-cultural landscape. It also applies data visualization to explore data preprocessing and analysis, data-driven storytelling, interactive dashboards, visual analytics, and advanced topics in data visualization. You'll gain insight into data-driven analysis of sentiment analysis and opinion mining, data-driven storytelling, and interactive visualization. Furthermore, the content discusses data visualization-based insights into data visualization applications and future trends, along with a capstone project in data visualization.The course includes multiple global data visualization projects, resources like formats, templates, worksheets, reading materials, quizzes, self-assessment, case studies, and assignments to nurture and upgrade your global data visualization and storytelling knowledge in detail.Course Content:Introduction and Study Plan● Introduction and know your Instructor● Study Plan and Structure of the Course1. Introduction to Data Visualization1.1.1 Introduction to Data Visualization1.1.2 Why Data Visualization1.1.3 Types of Data Visualization1.1.4 Tools for Data Visualization1.1.5 Best Practices for Data Visualization1.1.6 Conclusion2. Data Types and Visualization Techniques2.1.1 Data Types and Visualization Techniques2.1.2 Numerical Data2.1.3 Categorical Data2.1.4 Time Series Data2.1.5 Text Data2.1.6 Geospatial Data2.1.7 Conclusion3. Data Preparation and Cleaning for Visualization3.1.1 Data Preparation and Cleaning for Visualization3.1.2 Data Collection3.1.3 Data Integration3.1.4 Data Quality Assurance3.1.5 Data Visualization3.1.6 Conclusion4. Exploratory Data Analysis (EDA)4.1.1 Exploratory Data Analysis (EDA)4.1.2 Data Collection and Familiarization4.1.3 Data Visualization4.1.4 Feature Engineering4.1.5 Iterative Process4.1.6 Conclusion5. Advanced Data Visualization Techniques5.1.1 Advanced Data Visualization Techniques5.1.2 Interactive Visualizations5.1.3 Parallel Coordinates5.1.4 Network Graphs5.1.5 Augmented Reality(AR) and Virtual Reality (VR5.1.6 Conclusion6. Visualizing Uncertainty and Projections6.1.1 Visualizing Uncertainty and Projections6.1.2 Error Bars6.1.3 Prediction Intervals6.1.4 Heatmaps with Uncertainty Bands6.1.4 Animated Visualizations6.1.5 Conclusion7. Storytelling with Data7.1.1 Storytelling with Data7.1.2 Know Your Audience7.1.3 Use Engaging Visuals7.1.4 Add Storytelling Elements7.1.5 Practice Ethical Data Storytelling7.1.6 Conclusion8. Design Principles and Aesthetics8.1.1 Design Principles and Aesthetics8.1.2 Clarity and Simplicity8.1.3 Color Choice8.1.4 Gestalt Principles8.1.4 Continuation of Gestalt Principles8.1.5 Conclusion9. Ethical and Responsible Data Visualization9.1.1 Ethical and Responsible Data Visualization9.1.2 Accuracy and Truthfulness9.1.3 Fairness and Equity9.1.4 Consent and Respect9.1.6 Continuous Learning and Improvement9.1.7 Conclusion10. Data Visualization Tools and Technologies10.1.1 Data Visualization Tools and Technologies10.1.2 General-purpose Visualization Tools10.1.3 Specialized Visualization Tools10.1.4 Programming Libraries and Frameworks10.1.5 Business Intelligence (BI) Platforms10.1.6 Conclusion11. Capstone Project11.1.1 Capstone Project11.1.2 Project Overview11.1.3 Visualization Design11.1.4 Interactive Elements11.1.5 Presentation and Documentation11.1.6 ConclusionAssignmentsStudent's Academic Performance Dataset (xAPI-Edu-Data)Data Visualization for Exploratory Data Analysis of the Titanic Dataset
