Capstone: Retrieving, Processing, and Visualizing Data with Python
- 4.7
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Approx. 9 hours to complete
Course Summary
Learn how to create interactive data visualizations using Python. This course covers various libraries and tools like Matplotlib, Seaborn, Plotly, and more.Key Learning Points
- Create different types of data visualizations using Python libraries
- Use visualization techniques to explore and understand complex data
- Build interactive dashboards and web applications to showcase data
Job Positions & Salaries of people who have taken this course might have
- USA: $62,453 - $94,000
- India: ₹347,000 - ₹1,132,000
- Spain: €24,000 - €45,000
- USA: $62,453 - $94,000
- India: ₹347,000 - ₹1,132,000
- Spain: €24,000 - €45,000
- USA: $85,000 - $139,000
- India: ₹450,000 - ₹2,000,000
- Spain: €32,000 - €60,000
- USA: $62,453 - $94,000
- India: ₹347,000 - ₹1,132,000
- Spain: €24,000 - €45,000
- USA: $85,000 - $139,000
- India: ₹450,000 - ₹2,000,000
- Spain: €32,000 - €60,000
- USA: $65,000 - $105,000
- India: ₹350,000 - ₹1,400,000
- Spain: €23,000 - €42,000
Related Topics for further study
Learning Outcomes
- Create interactive visualizations using Python libraries
- Understand data visualization techniques to explore complex data
- Build interactive dashboards and web applications to showcase data
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of Python programming
- Familiarity with data analysis and visualization concepts
Course Difficulty Level
IntermediateCourse Format
- Online self-paced course
- Video lectures
- Hands-on projects
- Quizzes and assessments
Similar Courses
- Data Visualization with Python
- Applied Data Visualization with Python
Related Education Paths
Notable People in This Field
- Chief Scientist at RStudio
- Statistician and Professor Emeritus at Yale University
Related Books
Description
In the capstone, students will build a series of applications to retrieve, process and visualize data using Python. The projects will involve all the elements of the specialization. In the first part of the capstone, students will do some visualizations to become familiar with the technologies in use and then will pursue their own project to visualize some other data that they have or can find. Chapters 15 and 16 from the book “Python for Everybody” will serve as the backbone for the capstone. This course covers Python 3.
Knowledge
- Make use of unicode characters and strings
- Understand the basics of building a search engine
- Select and process the data of your choice
- Create email data visualizations
Outline
- Welcome to the Capstone
- Introduction: Welcome to the Class
- Unicode Characters and Strings
- Office Hours in Den Haag, Netherlands
- Interview: John Resig and Pam Fox - Khan Academy
- Capstone Overview
- Help Us Learn More About You!
- Python Textbook
- Coming from Python 2 - Encoding Data in Python 3
- Capstone Completion Options
- Building a Search Engine
- Page Rank Overview
- Worked Example: Page Rank - Spidering (Chapter 16)
- Worked Example: Page Rank - Computation (Chapter 16)
- Worked Example: Page Rank - Visualization (Chapter 16)
- Office Hours Detroit, Michigan
- Interview: Anil Jain - Image Processing
- Building a Search Engine - Introduction
- Peer Graded Assignment - Instructor Input
- Exploring Data Sources (Project)
- Dr. Chuck's New Kitten - Sakaiger
- Interview: Bruce Schneier - The Security Mindset
- Identifying Your Data Source - Introduction
- List of Data Sources (Instructional Staff Curated)
- Spidering and Modeling Email Data
- Gmane Introduction
- Worked Example: Gmane / Mail - Retrieval (Chapter 16)
- Worked Example: Gmane / Mail - Model (Chapter 16)
- Office Hours Baltimore, MD
- Interview: Bruce Schneier - Building Cryptographic Systems
- Spidering and Modeling Email Data - Introduction
- Accessing New Data Sources (Project)
- Office Hours: Dr. Chuck Pretends to be Anthony Bourdain
- Accessing New Data Sources - Introduction
- Visualizing Email Data
- Worked Example: Gmane / Mail - Visualization (Chapter 16)
- Office Hours, Montreal, Canada
- Interview: Nathaniel Borenstein - The Father of MIME
- Visualizing Email Data
- Visualizing new Data Sources (Project)
- Office Hours - Dr. Chuck's Office - Ann Arbor, Michigan
- Video: Steve Jobs, NeXT and the Internet
- Visualizing new Data Sources - Introduction
- Post-Course Survey
Summary of User Reviews
Python Data Visualization course on Coursera has received positive reviews from users. The course is highly recommended by many users who found it informative and useful in visualizing data. They have rated the course highly for its comprehensive coverage of the topic.Key Aspect Users Liked About This Course
Many users found the course's coverage of data visualization to be comprehensive and informative.Pros from User Reviews
- The course provides a good introduction to data visualization with Python.
- The instructors are knowledgeable and engaging.
- The course offers practical examples that are relevant to real-world scenarios.
- The course is well-structured and easy to follow.
- The course provides a good foundation for further study in data visualization.
Cons from User Reviews
- Some users found the pace of the course to be too slow or too fast.
- Some users felt that the course could have provided more hands-on exercises.
- Some users found the course content to be too basic and not suitable for more advanced learners.
- Some users found the course to be too theoretical and lacking in practical applications.
- Some users experienced technical issues with the course platform.
Charles Russell Severance
4.7 Raiting
Capstone: Retrieving, Processing, and Visualizing Data with Python
- 4.7
-
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