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⇱ Clean, Analyze, and Visualize Your Data | Coursera


Clean, Analyze, and Visualize Your Data

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Clean, Analyze, and Visualize Your Data

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Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

2 hours to complete
Flexible schedule
Learn at your own pace

Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

2 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Develop core data preparation and exploration skills for AI. Implement data validation and visualization to ensure high-quality data for models.

Details to know

Shareable certificate

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Recently updated!

December 2025

Assessments

3 assignments¹

AI Graded see disclaimer
Taught in English

Build your subject-matter expertise

This course is part of the Agentic AI Performance & Reliability Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • 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

There are 2 modules in this course

"Clean, Analyze, and Visualize Your Data" is an intermediate course designed for aspiring AI and data professionals who understand that world-class models are built on high-quality data. In this course, you will move beyond theory and gain hands-on experience in the essential, practical skills of data preparation and exploration. You will learn to implement systematic data cleaning and validation routines using industry-standard tools like Pandera to ensure your datasets are reliable and ready for processing.

Through guided labs in a Jupyter environment, you will master statistical visualization and dimensionality reduction techniques, such as t-SNE, to transform complex, high-dimensional data into clear, interpretable plots. These visualizations will empower you to uncover hidden patterns, identify anomalies, and diagnose issues—like misrouted data clusters—that could impact model accuracy. By the end of this course, you will not just know how to clean data, but you will understand how to analyze and visualize it to derive insights, ensuring your AI development is built on a solid, well-understood foundation.

This module lays the critical foundation for any AI project: data quality. You will immediately confront a data quality challenge to understand why cleaning is essential. You will then learn how to implement systematic routines using Python and the Pandera library to validate a dataset's structure, handle missing values, and prepare raw data so that it is reliable and ready for analysis.

What's included

1 video1 reading1 assignment1 ungraded lab

1 videoTotal 4 minutes
  • How to Build a Validation Schema with Pandera4 minutes
1 readingTotal 8 minutes
  • The Data Wrangler's Toolkit: Core Cleaning Concepts8 minutes
1 assignmentTotal 15 minutes
  • Data Validation and Imputation: Quiz 15 minutes
1 ungraded labTotal 20 minutes
  • Cleaning a Raw Customer Dataset20 minutes

High-dimensional data can hide important patterns. In this module, you will learn how to use dimensionality reduction techniques like t-SNE to visualize complex datasets. You will analyze these visualizations to uncover hidden clusters, identify outliers, and diagnose issues that are invisible in raw data, such as a misrouted intent cluster affecting model accuracy.

What's included

2 videos1 reading2 assignments1 ungraded lab

2 videosTotal 10 minutes
  • Seeing the Unseen: Finding a Hidden Error Cluster5 minutes
  • How to Create and Interpret a t-SNE Plot5 minutes
1 readingTotal 10 minutes
  • Taming the Dimensions: An Introduction to t-SNE and PCA10 minutes
2 assignmentsTotal 40 minutes
  • Report: From Data Cleaning to Visual Insight30 minutes
  • Analyzing a New Visualization 10 minutes
1 ungraded labTotal 20 minutes
  • Visualizing Message Embeddings to Find Errors20 minutes

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Frequently asked questions

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

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¹ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.