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 faz parte do Programa de cursos integrados Python para todosPython para todos
Trabalho de conclusão de curso: recuperação, processamento e visualização de dados com Python
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Informações sobre o curso
4.6
3,887 classificações
O que você vai aprender
Create email data visualizations
Make use of unicode characters and strings
Select and process the data of your choice
Understand the basics of building a search engine
Habilidades que você terá
Data AnalysisPython ProgrammingDatabase (DBMS)Data Visualization (DataViz)
Programa - O que você aprenderá com este curso
Semana
1Welcome 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.
4 vídeos (total de (Total 35 mín.) min), 5 leituras, 1 teste
4 videos
Unicode Characters and Strings17min
Office Hours in Den Haag, Netherlands3min
Interview: John Resig and Pam Fox - Khan Academy11min
5 leituras
Capstone Overview10min
Help Us Learn More About You!10min
Python Textbook10min
Coming from Python 2 - Encoding Data in Python 310min
Notice for Auditing Learners: Assignment Submission10min
1 exercícios práticos
Using Encoded Data in Python 310min
Semana
2Building 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 required 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.
6 vídeos (total de (Total 61 mín.) min), 2 leituras, 1 teste
6 videos
Worked Example: Page Rank - Spidering (Chapter 16)17min
Worked Example: Page Rank - Computation (Chapter 16)15min
Worked Example: Page Rank - Visualization (Chapter 16)6min
Office Hours Detroit, Michigan1min
Interview: Anil Jain - Image Processing11min
2 leituras
Building a Search Engine - Introduction10min
Peer Graded Assignment - Instructor Input10min
Semana
3Exploring 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.
2 vídeos (total de (Total 9 mín.) min), 2 leituras
2 leituras
Identifying Your Data Source - Introduction10min
List of Data Sources (Instructional Staff Curated)10min
Semana
4Spidering and Modeling Email Data
In our second required 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.
5 vídeos (total de (Total 49 mín.) min), 1 leitura, 1 teste
5 videos
Worked Example: Gmane / Mail - Retrieval (Chapter 16)17min
Worked Example: Gmane / Mail - Model (Chapter 16)12min
Office Hours Baltimore, MD1min
Interview: Bruce Schneier - Building Cryptographic Systems11min
1 leituras
Spidering and Modeling Email Data - Introduction10min
41%
comecei uma nova carreira após concluir estes cursos
39%
consegui um benefício significativo de carreira com este curso
18%
recebi um aumento ou promoção
Melhores avaliações
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(132)Informative course
(132)por JC•May 26th 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.
por NS•Apr 10th 2016
Python for everyone is One of the Best Course on MOOC platform .\n\nDr. Chuck made it interesting and Knowledgeable. Way back 3 Months ,I can't even thing of the stuff that I leaned and implemented .
Instrutores
Charles Severance
ProfessorSchool of Information
Sobre Universidade de 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.
Sobre o Programa de cursos integrados Python para todosPython 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.
Perguntas Frequentes – FAQ
Quando terei acesso às palestras e às tarefas?
Ao se inscrever para um Certificado, você terá acesso a todos os vídeos, testes e tarefas de programação (se aplicável). Tarefas avaliadas pelos colegas apenas podem ser enviadas e avaliadas após o início da sessão. Caso escolha explorar o curso sem adquiri-lo, talvez você não consiga acessar certas tarefas.
O que recebo ao me inscrever nesta Especialização?
Quando você se inscreve no curso, tem acesso a todos os cursos na Especialização e pode obter um certificado quando concluir o trabalho. Seu Certificado eletrônico será adicionado à sua página de Participações e você poderá imprimi-lo ou adicioná-lo ao seu perfil no LinkedIn. Se quiser apenas ler e assistir o conteúdo do curso, você poderá frequentá-lo como ouvinte sem custo.
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