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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-analyst-in-python-for-beginners/
课程评论：没有评论
课程名称：初学者的Python数据分析师 课程概述：本课程旨在培养学生掌握成为熟练数据分析师所需的基本技能和知识，使用Python编程语言进行数据分析。该综合性课程面向希望使用数据、提取有意义见解并做出数据驱动决策的个人。课程不要求学生具备编程或数据分析的先前经验。在整个课程中，学生将学习使用Python进行有效数据分析所必需的核心概念和技术。从数据获取和清洗到探索性数据分析、统计分析和数据可视化，学生将通过流行的Python库（如Pandas、NumPy、Matplotlib和Seaborn）获得动手实践经验，完成各种数据分析任务。 课程目标： 1. 理解数据分析的基本原理以及数据分析师在各行业中的角色。 2. 熟练掌握Python编程语言以进行数据分析任务。 3. 发展获取、清洗和预处理数据的技能。 4. 学习探索性数据分析（EDA）技术，以发现数据集中的模式、趋势和关系。 5. 应用统计分析技术，以得出有意义的结论并做出数据驱动的决策。 6. 掌握数据可视化的艺术，以有效传达见解和发现。 通过实际练习和项目，学生将获得在真实数据集上工作的实践Python技能。
The course is designed to equip students with the essential skills and knowledge required to become proficient data analysts using the Python programming language. This comprehensive course caters to individuals who aspire to work with data, derive meaningful insights, and make data-driven decisions. No prior experience in programming or data analysis is required.Throughout this course, students will learn the core concepts and techniques necessary for effective data analysis using Python. From data acquisition and cleaning to exploratory data analysis, statistical analysis, and data visualization, students will gain hands-on experience in performing a wide range of data analysis tasks using popular Python libraries such as Pandas, NumPy, Matplotlib, and Seaborn.Course Objectives:Understand the fundamentals of data analysis and the role of a data analyst in various industries.Acquire proficiency in using Python programming language for data analysis tasks.Develop skills in acquiring, cleaning, and preprocessing data for analysis.Learn exploratory data analysis (EDA) techniques to uncover patterns, trends, and relationships in datasets.Apply statistical analysis techniques to draw meaningful conclusions and make data-driven decisions.Master the art of data visualization to effectively communicate insights and findings. Gain the practical Python skills hands-on experience in working with real-world datasets through practical exercises and projects.
