数据分析实战课：用 Excel、Python 与 ChatGPT 高效掌握全流程技能

本课程整合 Excel、Python 与 ChatGPT 三大工具，全面覆盖数据分析的核心技能。从数据清洗、统计分析、可视化图表到实战演练，你将学会使用函数、Pandas、条件语句、透视表、回归分析等关键技巧，并通过 60+ 实战案例掌握解决真实业务问题的方法。课程零基础友好，适合初学者、职场人士与数据分析爱好者，帮助你系统构建从数据到决策的完整分析思维与实战能力。

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教程名称：Data Analysis 3 in 1: Excel, Python and ChatGPT

下载连结：https://www.nidown.com/chatgpt-297132.html

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英文原版介绍

Master Complete Data Analysis Workflow. Unleash Two Widely Used Tools – Excel and Python. Empower Yourself with ChatGPT.

What you’ll learn:

Learn Python’s syntax, data types, variables, and operators to construct simple programs and execute basic functions.
To manage program flow, use loops and conditional statements like if, elif, and else.
Learn to use Python lists, dictionaries, tuples, and sets.
Learn to access, change, and manipulate these structures for various programming needs.
Understand and apply techniques for cleaning and preparing raw data in Excel.
Learn to identify and handle missing data, outliers, and inconsistencies.
Utilize Excel functions and tools for data validation and transformation.
Explore fundamental statistical concepts and their application in Excel.
Learn to perform descriptive statistics, inferential statistics, and hypothesis testing using Excel functions and tools.
Understand how to interpret and communicate statistical results effectively.
Design and build interactive dashboards in Excel for effective data visualization.
Learn to use PivotTables, PivotCharts, and slicers to create dynamic and user-friendly dashboards.
Explore various data visualization techniques available in Excel, including charts, graphs.
Learn and apply the data analysis methodology, from data cleaning to hypothesis testing, in real-world applications.
Increase your critical thinking and problem-solving skills for data analysis, decision-making, and recommendation.
Use value counts, percentage, group by, pivot tables, correlation, and regression professionally and realistically.
Solve over 60+ real-world data analytical questions to practice applying data analysis to various circumstances.
Emphasize practical application to gain valuable insights from data and create educated judgments and suggestions.