Roadmap to Learn Excel for Data Science

Learning Excel is an unsaid rule for Data Science. People think that Excel is only used to record data, but in the real world, Excel is much more than that. So, if you want to know how to learn Excel for Data Science, this article is for you. In this article, I’ll take you through a step-by-step roadmap to learn Excel for Data Science.

Roadmap to Learn Excel for Data Science

The roadmap to learn Excel for Data Science can be divided into four steps:

Learn Excel Fundamentals
Master Excel Functions and Formulas
Learn Excel for Analysis and Visualization
Practice Excel Problems

Let’s go through each step of the roadmap in detail.

Step 1: Learn Excel Fundamentals

The first step is to familiarize yourself with Excel’s interface and basic functionalities. Key topics that you should learn are:

Excel interface (ribbons, menus, and toolbars)
Basic navigation and data entry
Formatting cells (fonts, colours, borders)
Basic arithmetic operations and formulas
Simple data manipulation (sorting and filtering)

Here’s a YouTube playlist by Leila Gharani on Excel for Beginners that you can follow.

Step 2: Master Excel Function and Formulas

The next step is to develop proficiency in using more complex functions and formulas. Key formulas and functions you should learn are:

Logical functions (IF, AND, OR)
Lookup functions (VLOOKUP, HLOOKUP, INDEX, MATCH)
Text functions (LEFT, RIGHT, MID, CONCATENATE, TRIM)
Date and time functions (TODAY, NOW, DATEDIF)
Statistical functions (AVERAGE, MEDIAN, MODE, STDEV)

Here’s a course on Problem-Solving with Excel by PwC that will help you learn all these functions and formulas in detail. You can also follow this free playlist on YouTube by Leila Gharani on advanced Excel formulas.

Step 3: Learn Excel for Data Analysis and Visualization

The next step is learning about how to analyze data and create meaningful visualizations using Excel. Key topics you should cover are:

PivotTables and PivotCharts
Data validation
Conditional formatting
Charts and graphs (bar, line, pie, scatter, etc.)
Data analysis tools:
- What-If Analysis
- Goal Seek
- Solver

Step 4: Practice Excel Problems

The next step is to practice challenging problems using Excel. Unlike SQL and Python, Excel doesn’t have a platform like Leet code where you can find challenges to solve problems using Excel. So below is an Excel practice file where you will find many problems to solve. I used this file as well when I used to learn Excel.

You can download this file on your system or practice these problems using Google Sheets as well.

Summary

So, here are the steps you should follow to learn Excel for Data Science:

Learn Excel Fundamentals
Master Excel Functions and Formulas
Learn Excel for Analysis and Visualization
Practice Excel Problems

I hope you liked this article on a roadmap to learn Excel for Data Science. Feel free to ask valuable questions in the comments section below. You can follow me on Instagram for many more resources.