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.
Este curso forma parte de Programa especializado: Python para todos
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Acerca de este Curso
Qué aprenderás
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
Habilidades que obtendrás
- Data Analysis
- Python Programming
- Database (DBMS)
- Data Visualization (DataViz)
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Universidad de Míchigan
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.
Programa - Qué aprenderás en este curso
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.
Reseñas
- 5 stars81,43 %
- 4 stars12,83 %
- 3 stars3,60 %
- 2 stars1,15 %
- 1 star0,96 %
Aspectos destacados
Principales reseñas sobre CAPSTONE: RETRIEVING, PROCESSING, AND VISUALIZING DATA WITH PYTHON
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 .
Good approach, If you are hurry to complete the certificate then it this course is for you. And even if you want to spend alot time to explore python then also this course is for you.
Great course. Nice introduction as a capstone course. Give all the programs a journal students needed. However, don't have the peer review for the self-study project make it's easier to pass.
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.
Acerca de Programa especializado: Python para todos
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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