Capstone: Retrieving, Processing, and Visualizing Data with Python

Start Date: 07/05/2020

Course Type: Common Course

Course Link:

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About Course

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.

Course Syllabus

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.

Deep Learning Specialization on Coursera

Course Introduction

Capstone: Retrieving, Processing, and Visualizing Data with Python In the capstone, you will design a system that will allow an IPython notebook to visualize and process data. You will use many of the same concepts as in the regular Capstone, but with a slightly different set of objectives. In the assignment, you will use the IPython Notebook as the main computer. This will allow you to use many of the same features as the regular Capstone, but at a much higher level of abstraction. This is the beginning of the Capstone where you will continue to improve your design as you learn how to use the IPython Notebook as the main computer. This is the beginning of the Capstone where you will use every tool and technology that is available to you to solve problems and design a system from scratch. This is a tremendously valuable and valuable experience to have.Protecting Your IPython Notebook from Unauthorized Use Protecting Your IPython Notebook from Smashes Protecting Your IPython Notebook from Fragile Software Enhancing Your Security Capital Budgeting In this course, learners will develop an understanding of how to select the best capital investment for their organization. They will learn the factors that affect the profitability of the corporation’s capital investments. They will also learn the factors that affect the cash flows from the corporation’s capital investments. This course is an introduction to investment economics as it relates to

Course Tag

Data Analysis Python Programming Database (DBMS) Data Visualization (DataViz)

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Data processing The term "data processing" has mostly been subsumed by the newer and somewhat more general term "information technology" (IT). The term "data processing" is presently considered sometimes to have a negative connotation, suggesting use of older technologies. As an example, during 1996 the "Data Processing Management Association" (DPMA) changed its name to the "Association of Information Technology Professionals". Nevertheless, the terms are approximately synonymous.
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Data processing For science or engineering, the terms "data processing" and "information systems" are considered too broad, and the more specialized term data analysis is typically used.
Data processing The term Data processing (DP) has also been used previously to refer to a department within an organization responsible for the operation of data processing applications.
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