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.
This course is part of the Python for Everybody Specialization
Offered By
Python for Everybody SpecializationUniversity of MichiganAbout this Course
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Learner Career Outcomes
38%
started a new career after completing these courses
38%
got a tangible career benefit from this course
19%
got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 5 of 5 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Approx. 9 hours to complete
English
Subtitles: English, Korean
What you will 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
Skills you will gain
Data AnalysisPython ProgrammingDatabase (DBMS)Data Visualization (DataViz)
Learner Career Outcomes
38%
started a new career after completing these courses
38%
got a tangible career benefit from this course
19%
got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 5 of 5 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Approx. 9 hours to complete
English
Subtitles: English, Korean
Offered by
University of Michigan
The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future.
Syllabus - What you will learn from this course
1 hour to complete
Welcome to the Capstone
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.
1 hour to complete
4 videos (Total 36 min), 5 readings, 1 quiz
4 videos
Unicode Characters and Strings17m
Office Hours in Den Haag, Netherlands3m
Interview: John Resig and Pam Fox - Khan Academy11m
5 readings
Capstone Overview10m
Help Us Learn More About You!10m
Python Textbook10m
Coming from Python 2 - Encoding Data in Python 310m
Capstone Completion Options10m
1 practice exercise
Python for Everybody - A Review
2 hours to complete
Building a Search Engine
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.
2 hours to complete
6 videos (Total 61 min), 2 readings, 1 quiz
6 videos
Worked Example: Page Rank - Spidering (Chapter 16)17m
Worked Example: Page Rank - Computation (Chapter 16)15m
Worked Example: Page Rank - Visualization (Chapter 16)6m
Office Hours Detroit, Michigan1m
Interview: Anil Jain - Image Processing11m
2 readings
Building a Search Engine - Introduction10m
Peer Graded Assignment - Instructor Input10m
1 hour to complete
Exploring Data Sources (Project)
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.
1 hour to complete
2 videos (Total 9 min), 2 readings
2 readings
Identifying Your Data Source - Introduction10m
List of Data Sources (Instructional Staff Curated)10m
2 hours to complete
Spidering and Modeling Email Data
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.
2 hours to complete
5 videos (Total 49 min), 1 reading, 1 quiz
5 videos
Worked Example: Gmane / Mail - Retrieval (Chapter 16)17m
Worked Example: Gmane / Mail - Model (Chapter 16)12m
Office Hours Baltimore, MD1m
Interview: Bruce Schneier - Building Cryptographic Systems11m
1 reading
Spidering and Modeling Email Data - Introduction10m
Reviews
TOP REVIEWS FROM CAPSTONE: RETRIEVING, PROCESSING, AND VISUALIZING DATA WITH PYTHON
by BCApr 28, 2020
Now I understand how data mining, API's and dumping and retrieving data from a database works. Excellent course to start understanding how python can be used to work with data sources on the internet.
by JCMay 25, 2017
I found this course a little bit easier that some of the previous courses, however, it allowed me to gain experience managing a larger projects that encompass several languages and multiple programs.
by NSApr 9, 2016
Python for everyone is One of the Best Course on MOOC platform . Dr. Chuck made it interesting and Knowledgeable. Way back 3 Months ,I can't even thing of the stuff that I leaned and implemented .
by RGOct 30, 2017
Excellent certificate; the project was a bit too easy, but I guess its purpose was to show that something seemingly complex was the result of breaking things into simpler and more manageable pieces.
About the Python for Everybody Specialization
This Specialization builds on the success of the Python for Everybody course and will introduce fundamental programming concepts including data structures, networked application program interfaces, and databases, using the Python programming language. In the Capstone Project, you’ll use the technologies learned throughout the Specialization to design and create your own applications for data retrieval, processing, and visualization.
Frequently Asked Questions
When will I have access to the lectures and assignments?
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- 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.
What will I get if I subscribe to this Specialization?
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. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Is financial aid available?
Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.
Will I earn university credit for completing the Course?
This Course doesn't carry university credit, but some universities may choose to accept Course Certificates for credit. Check with your institution to learn more. Online Degrees and Mastertrack™ Certificates on Coursera provide the opportunity to earn university credit.
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