University of Michigan
Capstone: Retrieving, Processing, and Visualizing Data with Python
University of Michigan

Capstone: Retrieving, Processing, and Visualizing Data with Python

295,117 already enrolled

Included with Coursera Plus

Gain insight into a topic and learn the fundamentals.
4.7

(13,960 reviews)

Beginner level
No prior experience required
Flexible schedule
Approx. 9 hours
Learn at your own pace
98%
Most learners liked this course
Gain insight into a topic and learn the fundamentals.
4.7

(13,960 reviews)

Beginner level
No prior experience required
Flexible schedule
Approx. 9 hours
Learn at your own pace
98%
Most learners liked this course

What you'll learn

  • 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

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

1 assignment

Taught in English

See how employees at top companies are mastering in-demand skills

Placeholder

Build your subject-matter expertise

This course is part of the Python for Everybody 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
Placeholder
Placeholder

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV

Share it on social media and in your performance review

Placeholder

There are 7 modules in this course

Congratulations to everyone for making it this far. Before you begin, please view the Introduction video and read the Capstone Overview. The Course Resources section contains additional course-wide material that you may want to refer to in future weeks.

What's included

4 videos5 readings1 assignment

This week we will download and run a simple version of the Google PageRank Algorithm and practice spidering some content. The assignment is peer-graded, and the first of three optional Honors assignments in the course. This a continuation of the material covered in Course 4 of the specialization, and is based on Chapter 16 of the textbook.

What's included

6 videos2 readings1 app item

The optional Capstone project is your opportunity to select, process, and visualize the data of your choice, and receive feedback from your peers. The project is not graded, and can be as simple or complex as you like. This week's assignment is to identify a data source and make a short discussion forum post describing the data source and outlining some possible analysis that could be done with it. You will not be required to use the data source presented here for your actual analysis.

What's included

2 videos2 readings1 discussion prompt

In our second optional Honors assignment, we will retrieve and process email data from the Sakai open source project. Video lectures will walk you through the process of retrieving, cleaning up, and modeling the data.

What's included

5 videos1 reading1 app item

The task for this week is to make a discussion thread post that reflects the progress you have made to date in retrieving and cleaning up your data source so can perform your analysis. Feedback from other students is encouraged to help you refine the process.

What's included

1 video1 reading1 discussion prompt

In the final optional Honors assignment, we will do two visualizations of the email data you have retrieved and processed: a word cloud to visualize the frequency distribution and a timeline to show how the data is changing over time.

What's included

3 videos1 reading1 app item

This week you will discuss the analysis of your data to the class. While many of the projects will result in a visualization of the data, any other results of analyzing the data are equally valued, so use whatever form of analysis and display is most appropriate to the data set you have selected.

What's included

2 videos3 readings1 discussion prompt

Instructor

Instructor ratings
4.9 (1,090 ratings)
Charles Russell Severance
University of Michigan
60 Courses4,400,571 learners

Offered by

Recommended if you're interested in Data Analysis

Prepare for a degree

Taking this course by University of Michigan may provide you with a preview of the topics, materials and instructors in a related degree program which can help you decide if the topic or university is right for you.

Why people choose Coursera for their career

Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."

Learner reviews

4.7

13,960 reviews

  • 5 stars

    82.26%

  • 4 stars

    12.38%

  • 3 stars

    3.37%

  • 2 stars

    1.05%

  • 1 star

    0.92%

Showing 3 of 13960

BC
5

Reviewed on Apr 28, 2020

NS
5

Reviewed on Apr 9, 2016

SJ
5

Reviewed on May 30, 2020

New to Data Analysis? Start here.

Placeholder

Open new doors with Coursera Plus

Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription

Advance your career with an online degree

Earn a degree from world-class universities - 100% online

Join over 3,400 global companies that choose Coursera for Business

Upskill your employees to excel in the digital economy

Frequently asked questions