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Master Data Cleaning in 2026
Master Data Cleaning with hands-on projects and real-world examples
By Rahul Verma
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Intermediate
English
0 learners
What you'll learn
- Understand the core concepts of Data Cleaning and how they fit together
- Build hands-on projects using Data Cleaning that you can add to your portfolio
- Apply Data Cleaning to solve real, practical problems in Data Science & AI
- Follow industry best practices and avoid common Data Cleaning mistakes
- Gain the confidence to use Data Cleaning at work and in interviews
Skills you'll gain
Data Cleaning
Practical Projects
Debugging
Best Practices
Problem Solving
Data Analysis
About this course
Want to get genuinely good at Data Cleaning? This practical course in our Data Science & AI track takes you from the essentials to applied, real-world skills. You'll learn by building — not just watching — with downloadable resources and exercises throughout. Rahul Verma guides you step by step through Data Analysis, focusing on the skills employers actually look for. Finish ready to put Data Cleaning on your resume and use it with confidence.
Curriculum
Getting Started
- Welcome and what you'll build video · 10:00 ▶ Free preview
- Data Cleaning in 10 minutes video · 11:00 ▶ Free preview
- Your first Data Cleaning walkthrough video · 12:00
- Hands-on exercise video · 13:00
Core Concepts
- Common patterns in practice video · 17:00
- Building the project — part 1 video · 06:00
- Debugging and troubleshooting video · 07:00
- Performance and optimisation video · 08:00
- Testing your work video · 09:00
Hands-On Practice
- Performance and optimisation video · 12:00
- Testing your work video · 13:00
- Welcome and what you'll build video · 14:00
Building Real Projects
- Welcome and what you'll build video · 07:00
- Data Cleaning in 10 minutes video · 08:00
- Your first Data Cleaning walkthrough video · 09:00
- Hands-on exercise video · 10:00
Going Deeper
- Common patterns in practice video · 14:00
- Building the project — part 1 video · 15:00
- Debugging and troubleshooting video · 16:00
- Performance and optimisation video · 17:00
- Testing your work video · 06:00