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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-analysis-in-tamil/
课程评论：没有评论
课程名称：数据分析（泰米尔语） 课程概述：本课程介绍了数据分析的基本概念和技术。参与者将学习如何收集、清理、分析和解释数据，以提取有意义的见解并支持决策。课程涵盖了理论概念和实践应用，帮助学生具备在各个领域有效处理数据的技能。 课程目标： 1. 理解数据分析基础：掌握数据分析的原则和方法，包括数据收集、清理、转换和可视化。 2. 学习统计技术：探索基本的统计技术以总结数据、识别模式和进行推断。 3. 精通数据清理和准备：学习如何清理和预处理数据，以确保分析的准确性和可靠性。 4. 探索数据可视化：发现有效可视化数据的各种技术，包括图表、图形和仪表板。 5. 发展分析技能：获得使用分析工具和软件（如Excel和Python）进行数据分析的实践经验。 6. 应用分析技术：在不同领域（包括商业、医疗和社会科学）的真实数据集和案例研究中实践应用分析技术。 课程主题： - 数据分析简介 - 数据收集与获取 - 数据清理与预处理 - 描述性统计与可视化 - 探索性数据分析 - 统计推断 - 数据可视化技术 先决条件：不需要先前的数据分析经验，但建议具备基本的数学概念和计算机使用能力。
This course provides an introduction to the fundamental concepts and techniques of data analysis. Participants will learn how to collect, clean, analyze, and interpret data to extract meaningful insights and support decision-making. The course covers both theoretical concepts and practical applications, equipping students with the skills necessary to work with data effectively in various domains.Course Objectives:Understand Data Analysis Fundamentals: Gain a solid understanding of the principles and methods of data analysis, including data collection, cleaning, transformation, and visualization.Learn Statistical Techniques: Explore basic statistical techniques for summarizing data, identifying patterns, and making inferences.Master Data Cleaning and Preparation: Learn how to clean and preprocess data to ensure accuracy and reliability for analysis.Explore Data Visualization: Discover various techniques for visualizing data effectively, including charts, graphs, and dashboards.Develop Analytical Skills: Acquire hands-on experience with analytical tools and software for data analysis, such as Excel, PythonApply Analytical Techniques: Practice applying analytical techniques to real-world datasets and case studies across different domains, including business, healthcare, and social sciences.Course Topics:Introduction to Data AnalysisData Collection and AcquisitionData Cleaning and PreprocessingDescriptive Statistics and VisualizationExploratory Data AnalysisStatistical InferenceData Visualization TechniquesPrerequisites:No prior experience with data analysis is required, but familiarity with basic mathematical concepts and computer literacy is recommended.
