Master Data Cleaning: Python, Excel & Power Query

Master Data Cleaning: Python, Excel & Power Query udemy course free download

Master practical data cleaning skills with Excel formulas, Power Query automation, and Python scripts.

Master Data Cleaning: Python, Excel & Power Query

The Complete Guide to Cleaning, Transforming, and Preparing Real-World Datasets for Analysis

Are you tired of spending hours cleaning messy spreadsheets or trying to make sense of inconsistent data? Do you want to master the essential data wrangling skills that professionals use every day to turn chaotic raw data into clean, structured datasets ready for analysis?

You’ve found the right course.

Whether you're a beginner, a data enthusiast, or a working professional looking to improve your data handling skills, this course will teach you how to clean and transform real-world data using Microsoft Excel, Power Query, and Python (pandas) — all with hands-on projects and real business scenarios.

What This Course Teaches You

Data cleaning is not glamorous, but it's one of the most critical steps in the data lifecycle. Without clean data, your dashboards, reports, and machine learning models will all suffer.

This course helps you develop a toolbox of techniques to clean, validate, merge, and prepare datasets — no matter where the data comes from.

By the end of the course, you’ll confidently handle:

• Duplicate entries

• Inconsistent text formats

• Missing or blank fields

• Merging messy datasets

• Reconciliations (like sales vs. inventory)

• Transforming dirty Excel or CSV files into clean data tables

We’ll show you how to solve these problems using:

• Excel formulas like IF(), TRIM(), TEXT(), and VLOOKUP()

• Power Query for automated and repeatable transformations

• Python’s pandas library for efficient, code-based data cleaning

Tools Covered

I focus on the three most widely used data cleaning tools:

1. Microsoft Excel
   Great for ad-hoc cleaning and understanding patterns quickly. You’ll learn how to:

   • Use formulas for detecting and fixing issues

   • Apply data validation

   • Use PivotTables for quick aggregations

2. Power Query (Excel/Power BI)
   Ideal for automating the cleanup process. You'll learn to:

   • Import and transform messy files

   • Normalize headers, split/merge columns

   • Remove blanks and errors with one-click transformations

3. Python (pandas)
   The industry-standard tool for scalable data cleaning. You’ll learn:

   • How to load and inspect messy datasets

   • Use dropna(), fillna(), replace(), str.lower(), and more

   • Merge datasets and handle duplicates with ease

No prior coding experience is required — we guide you step-by-step.

Who This Course Is For

This course is designed for a wide range of learners, including:

• Data analysts and business analysts who want to clean data faster and more reliably.

• Students and career switchers who want to build a data portfolio and gain practical skills.

• Excel users and non-programmers looking to upgrade to more powerful tools like Power Query and pandas.

• Consultants and freelancers who deal with messy client data and need repeatable workflows.

• Professionals in operations, finance, HR, sales, and marketing who deal with spreadsheets and CSVs every day.

What You’ll Learn (By Section)

1. Data Cleaning Basics

   • What makes data messy

   • Common formats, missing values, and inconsistencies

2. Excel for Data Cleaning

   • Cleaning with formulas: IF, TEXT, VLOOKUP, TRIM

   • Using filters, validation, and conditional formatting

3. Power Query for Automation

   • Loading data from folders and files

   • Splitting, merging, and unpivoting columns

   • Removing duplicates and fixing types

4. Python & pandas for Real-World Cleaning

   • Cleaning text columns

   • Removing duplicates

   • Dealing with nulls and formatting issues

   • Merging datasets with .merge() and .concat()

5. Capstone Projects

   • Clean messy HR datasets with inconsistent employee names and IDs

   • Reconcile sales vs. inventory using merges, grouping, and filters

   • Transform multiple Excel files into a unified clean dataset

Each project mimics a real job task you’ll face in the field — perfect for practice and your portfolio.

What You’ll Achieve

By the end of the course, you'll be able to:

• Confidently clean and prepare messy Excel/CSV data using industry tools

• Automate data cleaning workflows using Power Query and pandas

• Merge multiple datasets with inconsistent IDs or formatting

• Spot and resolve real-world issues like duplicates, bad formatting, and null values

• Build reusable scripts and queries for repeatable processes

• Present clean, analysis-ready data for reporting or machine learning

What’s Included

• Step-by-step lessons with examples

• 4+ real-world datasets to practice on

Why This Course Is Different

This isn’t just theory — it’s hands-on learning from the ground up. I don’t just show you tools; we show you how to use them in the messy, imperfect world of real business data.

Each section ends with practical challenges and mini-projects to reinforce your skills. You’ll walk away not just knowing what to do, but why it works.

Ready to Master Data Cleaning?

Whether you're building dashboards, preparing reports, or feeding a data pipeline — clean data is your foundation.

Enroll now and start cleaning smarter — not harder.
Learn Excel, Power Query, and Python the practical way.