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
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Financial Data Analysis with Excel, Python and Power BI
This course is part of Financial Analyst: AI, Excel, and Power BI Skills Professional Certificate

Instructor: Professionals from the Industry
Included with
Recommended experience
What you'll learn
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
Details to know

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March 2026
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Build your Data Analysis expertise
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate from Coursera

There are 15 modules in this course
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.
What's included
3 videos1 reading2 assignments
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.
What's included
2 videos1 reading2 assignments
You will recognize the core components within a business intelligence suite and understand how they connect to financial reporting workflows.
What's included
3 videos1 reading1 assignment
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.
What's included
2 videos1 reading2 assignments
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.
What's included
3 videos1 reading1 assignment
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.
What's included
2 videos1 reading2 assignments
You will recall commands to manage packages and inspect data frames. You’ll review data structure and confirm readiness for categorical analysis.
What's included
4 videos1 reading1 assignment
You will apply frequency analysis to summarize the distribution of categorical data. You’ll interpret patterns and prepare results for reporting.
What's included
2 videos1 reading2 assignments
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.
What's included
3 videos1 reading2 assignments
You will apply data import tools to transform semi-structured JSON into a tabular format. You’ll automate transformation workflows to support scalable reporting.
What's included
2 videos1 reading2 assignments
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.
What's included
2 videos3 readings1 assignment
You will apply row-level security rules to a published report. You’ll ensure sensitive financial information remains protected while supporting collaboration.
What's included
3 videos1 reading2 assignments
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.
What's included
3 videos1 reading1 assignment
You will apply advanced lookup formulas to create flexible data retrieval tools. You’ll design dynamic templates that retrieve financial data efficiently and accurately.
What's included
2 videos1 reading2 assignments
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.
What's included
2 readings1 assignment
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Frequently asked questions
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.
More questions
Financial aid available,
¹ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.





