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 for Everybody
Capstone: Retrieving, Processing, and Visualizing Data with Python
ofrecido por
Acerca de este Curso
91,745 vistas recientes
Qué aprenderás
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 obtendrás
Data AnalysisPython ProgrammingDatabase (DBMS)Data Visualization (DataViz)
Programa - Qué aprenderás en este curso
Semana
12 horas para completar
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.
4 videos (Total 35 minutos), 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 lecturas
Capstone Overview10m
Help Us Learn More About You!10m
Python Textbook10m
Coming from Python 2 - Encoding Data in Python 310m
Notice for Auditing Learners: Assignment Submission10m
1 ejercicio de práctica
Using Encoded Data in Python 310m
Semana
22 horas para completar
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 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 videos (Total 61 minutos), 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 lecturas
Building a Search Engine - Introduction10m
Peer Graded Assignment - Instructor Input10m
Semana
31 hora para completar
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.
2 videos (Total 9 minutos), 2 readings
2 lecturas
Identifying Your Data Source - Introduction10m
List of Data Sources (Instructional Staff Curated)10m
Semana
42 horas para completar
Spidering 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 videos (Total 49 minutos), 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 lectura
Spidering and Modeling Email Data - Introduction10m
41%
comenzó una nueva carrera después de completar estos cursos
40%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
19%
consiguió un aumento de sueldo o ascenso
Principales revisiones sobre Capstone: Retrieving, Processing, and Visualizing Data with Python
Aspectos destacados
Informative course
(132)Relevant project
(132)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.
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 .
Instructor
Charles Severance
ProfessorSchool of Information
Acerca de 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.
Acerca del programa especializado Python for Everybody
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.
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.
¿Qué recibiré si me suscribo a este Programa especializado?
Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.
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