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.
Dieser Kurs ist Teil der Spezialisierung Spezialisierung Python für alle
von
Über diesen Kurs
Was Sie lernen werden
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
Kompetenzen, die Sie erwerben
- Data Analysis
- Python Programming
- Database (DBMS)
- Data Visualization (DataViz)
von

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.
Lehrplan - Was Sie in diesem Kurs lernen werden
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.
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.
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.
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.
Bewertungen
- 5 stars81,35 %
- 4 stars12,87 %
- 3 stars3,63 %
- 2 stars1,15 %
- 1 star0,97 %
Highlights
Top-Bewertungen von CAPSTONE: RETRIEVING, PROCESSING, AND VISUALIZING DATA WITH PYTHON
Really great sample code for working on other projects in the future. Good wrap up to the specialization. I was hoping there was more code editing required to complete the three assignments.
This whole specialisation is really well planned and simple enough to follow through. Kudos to the instructor who is engaging and able to distil difficult concepts down to something simpler.
Its very Important concept while we dealing with Databases. I am feeling happy that learn this retrieving,processing,Visualizing concepts with python environment. Thanks COURSERA TEAM
Wow, It's been great learning the course material. I am so happy to have had the opportunity to learn this all from Dr. Chuck. I have a new skill set and a new appreciation for programming.
Über den Spezialisierung Python für alle
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.

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