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Data Analysis and Visualization with Python

Learn to analyze and visualize data using Python libraries like NumPy, Pandas, and Matplotlib. Perfect for beginners in data analysis.

Learn to analyze and visualize data using Python libraries like NumPy, Pandas, and Matplotlib. Perfect for beginners in data analysis.

This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Python: A Guided Journey from Introduction to Application Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.

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Data Analysis and Visualization with Python

This course includes

16 Hours

Of Self-paced video lessons

Beginner Level

Completion Certificate

awarded on course completion

Free course

What you'll learn

  • Analyze data using Python libraries and tools

  • Create effective data visualizations

  • Manipulate and process large datasets

  • Handle file operations and exceptions

  • Use data structures for analysis

Skills you'll gain

Data Analysis
Python Programming
Data Visualization
NumPy
Pandas
Matplotlib
File Handling
Exception Handling
Data Manipulation
Statistical Analysis

This course includes:

1.9 Hours PreRecorded video

12 quizzes

Access on Mobile, Tablet, Desktop

FullTime access

Shareable certificate

Get a Completion Certificate

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Certificate

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There are 3 modules in this course

This comprehensive course teaches data analysis and visualization using Python. Students learn to work with data structures like lists, tuples, dictionaries, and sets, while mastering essential libraries including NumPy, Pandas, and Matplotlib. The curriculum covers file input/output operations, data manipulation, and creating insightful visualizations. Topics include exception handling, data processing, and statistical analysis techniques.

Sequences

Module 1 · 6 Hours to complete

File Input and Output

Module 2 · 4 Hours to complete

Data Analysis

Module 3 · 5 Hours to complete

Fee Structure

Instructors

Adwith Malpe
Adwith Malpe

4,435 Students

4 Courses

Assistant Teaching Professor

Adwith Malpe is a Computer Engineer with a Master’s degree in Computer Engineering and a Bachelor’s in Computer Systems Engineering from Arizona State University. His industry experience spans both the financial and aerospace sectors, with a strong focus on Computer Science.

Steven Osburn
Steven Osburn

2,496 Students

2 Courses

Assistant Teaching Professor at Arizona State University

Steven Osburn is an Assistant Teaching Professor at Arizona State University, where he specializes in computer science and data analysis. He teaches courses such as "Data Analysis and Visualization with Python" and "Object-Oriented Programming and GUI with Python," focusing on equipping students with essential programming and analytical skills. His teaching approach emphasizes hands-on learning and practical applications, preparing students for real-world challenges in technology and data science.In addition to his teaching responsibilities, Steven is actively involved in curriculum development and student engagement initiatives within the Ira A. Fulton Schools of Engineering. His courses on Coursera are designed to make complex topics accessible to learners, helping them build a solid foundation in programming and data visualization techniques. Through his work, Steven aims to inspire the next generation of engineers and data scientists.

Data Analysis and Visualization with Python

This course includes

16 Hours

Of Self-paced video lessons

Beginner Level

Completion Certificate

awarded on course completion

Free course

Testimonials

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Frequently asked questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.