Clean, transform, analyze, and visualize financial data using Excel, Python, R, and Power BI. In this course, you’ll develop practical data analysis skills used by financial analysts to turn raw data into clear business insights.

Financial Data Analysis with Excel, Python and Power BI
包含在 中
您将学到什么
Clean and transform financial datasets using Excel and Python
Build interactive Power BI dashboards with secure data models
Apply statistical summaries and data visualization for financial reporting
您将获得的技能
要了解的详细信息
了解顶级公司的员工如何掌握热门技能

积累 Data Analysis 领域的专业知识
- 向行业专家学习新概念
- 获得对主题或工具的基础理解
- 通过实践项目培养工作相关技能
- 通过 Coursera 获得可共享的职业证书

该课程共有15个模块
You will recall the syntax for common spreadsheet functions and understand how they support accurate financial calculations. You’ll practice applying formulas correctly to ensure reliable budgeting and reporting.
涵盖的内容
3个视频1篇阅读材料2个作业
You will apply advanced spreadsheet functions to construct a financial budget template. You’ll automate summary values and compare actual results against targets to evaluate budget performance.
涵盖的内容
2个视频1篇阅读材料2个作业
You will recognize the core components within a business intelligence suite and understand how they connect to financial reporting workflows.
涵盖的内容
3个视频1篇阅读材料1个作业
You will apply data visualization tools to create and publish a chart from a dataset. You’ll refine visuals for clarity and share insights through Power BI Service.
涵盖的内容
2个视频1篇阅读材料2个作业
You will recognize the purpose of fundamental functions for data loading and initial inspection. You’ll explore dataset structure and identify potential quality issues before analysis.
涵盖的内容
3个视频1篇阅读材料1个作业
You will apply data cleaning techniques to a specified dataset using a computational notebook. You’ll standardize formats, resolve missing values, and prepare data for reliable analysis.
涵盖的内容
2个视频1篇阅读材料2个作业
You will recall commands to manage packages and inspect data frames. You’ll review data structure and confirm readiness for categorical analysis.
涵盖的内容
4个视频1篇阅读材料1个作业
You will apply frequency analysis to summarize the distribution of categorical data. You’ll interpret patterns and prepare results for reporting.
涵盖的内容
2个视频1篇阅读材料2个作业
You will recall the definitions and examples of structured, semi-structured, and unstructured data. You’ll understand how data structure affects financial reporting and governance.
涵盖的内容
3个视频1篇阅读材料2个作业
You will apply data import tools to transform semi-structured JSON into a tabular format. You’ll automate transformation workflows to support scalable reporting.
涵盖的内容
2个视频1篇阅读材料2个作业
You will create a star-schema data model by defining table relationships and calculated columns. You’ll structure financial datasets to support accurate and efficient reporting.
涵盖的内容
2个视频3篇阅读材料1个作业
You will apply row-level security rules to a published report. You’ll ensure sensitive financial information remains protected while supporting collaboration.
涵盖的内容
3个视频1篇阅读材料2个作业
You will apply Power Query to automate data cleansing and document the transformation logic. You’ll build repeatable workflows that reduce manual effort and improve reliability.
涵盖的内容
3个视频1篇阅读材料1个作业
You will apply advanced lookup formulas to create flexible data retrieval tools. You’ll design dynamic templates that retrieve financial data efficiently and accurately.
涵盖的内容
2个视频1篇阅读材料2个作业
In this project, you will clean and transform raw retail financial data and build a structured performance dashboard for executive review. You will standardize inconsistent data fields, convert semi-structured expense data into tabular format, and calculate key financial metrics including sales, cost of goods sold, and operating profit. Using the cleaned dataset, you will design a clear and professional dashboard that visualizes sales trends, expense breakdown, and store performance. You will also provide written insights explaining financial trends and the importance of data cleaning before analysis. This project simulates a real financial data transformation and reporting assignment commonly performed by entry-level financial and business analysts.
涵盖的内容
2篇阅读材料1个作业
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常见问题
Yes. The course introduces each tool step-by-step and explains how they are used in finance contexts. No prior programming experience is required.
No. Foundational concepts are introduced within the course. You’ll apply practical techniques focused on financial datasets.
Financial analysts often work across Excel, BI tools, and data processing scripts. This course builds hands-on skills in cleaning data, building dashboards, and presenting performance insights.
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¹ 本课程的部分作业采用 AI 评分。对于这些作业,将根据 Coursera 隐私声明使用您的数据。








