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Теория отраслевых рынков (Industrial Organization)

About this course: Курс посвящен факторам, влияющим на размер компаний и структуру рынка. Почему на одних рынках преобладают малые компании, а на другом крупные? Продавцы принимают решения стратегически, однако их стимулы в свою очередь зависят от структуры рынка и от предшествующих решений. Как разделить между зоной предопределенных и свободных решений? Например, сговор как модель ценового поведения – предопределен структурой рынка или служит результатом свободного волеизъявления? Способны ли укоренившиеся на рынке продавцы препятствовать входу новичков, защищая свою рыночную долю и свою прибыль? Каковы лучшие способы предотвращения ценовых сговоров продавцов? Нужно ли (или по крайней мере желательно) запрещать или ограничивать слияния между крупными продавцами? Есть ли необходимость для государственной политики налагать ограничения на условия договоров между производителем и дистрибьютором? Как в этих условиях должна быть организована государственная политика (применение антимоноп…

Learn to Program and Analyze Data with Python

Learn to Program and Analyze Data with Python
Develop programs to gather, clean, analyze, and visualize data

About This Specialization

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.
Created by:
courses
5 courses
Follow the suggested order or choose your own.
projects
Projects
Designed to help you practice and apply the skills you learn.
certificates
Certificates
Highlight your new skills on your resume or LinkedIn.
Courses
Beginner Specialization.
No prior experience required.

  1. COURSE 1

    Programming for Everybody (Getting Started with Python)

    Current session: May 15 — Jul 10.
    Commitment
    2-4 hours/week
    Subtitles
    English, Chinese (Simplified)

    About the Course

    This course aims to teach everyone the basics of programming computers using Python. We cover the basics of how one constructs a program from a series of simple instructions in Python. The course has no pre-requisites and avoids all but the simplest mathematics. Anyone with moderate computer experience should be able to master the materials in this course. This course will cover Chapters 1-5 of the textbook “Python for Informatics”. This course is equivalent to the first half of the 11-week "Programming for Everybody (Python)" course. Once a student completes this course, they will be ready to take more advanced programming courses. This course covers Python 2.
    Show or hide details about course Programming for Everybody (Getting Started with Python)

    WEEK 1
    Chapter One - Why we Program?
    These are the course-wide materials as well as the first part of Chapter One where we explore what it means to write programs. We finish Chapter One and have the quiz and first assignment in the third week of the class. Throughout the course you may want to come back and look at these materials. This section should not take you an entire week.
    Reading · Reading: Welcome to The Class
    Video · Video: Welcome to Class - Dr. Chuck
    Video · Video: Welcome to Python - Guido van Rossum
    Reading · Textbook: Python for Informatics: Exploring Information
    Video · Fun: The Textbook Authors Meet @PyCon2015
    Reading · Syllabus / Course Information
    Reading · About the New Platform
    Reading · Submitting Assignments
    Reading · Lecture Slides
    Video · Lecture 1.1 - Why Program
    Video · Lecture 1.2 Hardware Overview
    Video · Lecture 1.3 Python as a Language
    Reading · Audio Versions of All Lectures
    Reading · Privacy Policy
    Reading · Student Curated Notes
    Video · Thanks to All Who Helped Make this Class Possible

    WEEK 2
    Installing and Using Python
    In this module you will set things up so you can write Python programs. Not all activities in this module are required for this class so please read the "Using Python in this Class" material for details.
    Reading · Important Reading: Using Python in this Class
    Video · Demonstration: Using the Python Playground
    Other · Python Code Playground
    Video · Windows 8: Installing Python and Writing A Program
    Video · Windows 8: Taking Screen Shots
    Video · Macintosh: Using Python and Writing A Program
    Video · Macintosh: Taking Screen Shots
    Video · Using Python on a Raspberry Pi / Linux
    Video · Bonus: Eben Upton and the RaspBerry Pi
    Video · Windows Vista: Installing Python and Writing A Program
    Video · Windows Vista: Taking Screen Shots
    Practice Peer Review · Optional- Installing Python Screen Shots

    WEEK 3
    Chapter One: Why We Program (continued)
    In the first chapter we try to cover the "big picture" of programming so you get a "table of contents" of the rest of the book. Don't worry if not everything makes perfect sense the first time you hear it. This chapter is quite broad and you would benefit from reading the chapter in the book in addition to watching the lectures to help it all sink in. You might want to come back and re-watch these lectures after you have funished a few more chapters.
    Video · Lecture 1.4 Writing Paragraphs of Code
    Video · Lecture 1.5 An Animated Programming Story
    Quiz · Chapter 1
    Video · Demonstration: Doing the "Hello World" Assignment
    Other · Assignment: Write Hello World
    Video · Interview: Daphne Koller - Building Coursera
    Video · Face-to-Face Office Hours: Milan, Italy

    WEEK 4
    Chapter Two: Variables and Expressions
    In this chapter we cover how a program uses the computer's memory to store, retrieve and calculate information.
    Video · Lecture 2.1 Expressions
    Video · Lecture 2.2 Types
    Quiz · Chapter 2
    Other · Assignment 2.2
    Reading · Where is the worked exercise for Assignment 2.2?
    Other · Assignment: 2.3
    Video · Worked Exercise: 2.3
    Video · Interview: Pooja Sankar - Building Piazza
    Video · Office Hours: Mountain View, CA

    WEEK 5
    Chapter Three: Conditional Code
    In this section we move from sequential code that simply runs one line of code after another to conditional code where some steps are skipped. It is a very simple concept - but it is how computer software makes "choices".
    Video · Lecture 3.1 Conditional Statements
    Video · Lecture 3.2 Examples of Conditional Statements
    Video · Lecture 3.3 Try and Except
    Quiz · Chapter 3
    Other · Assignment: 3.1
    Video · Worked Exercise: 3.2
    Other · Assignment: 3.3
    Video · Interview: Massimo Banzi: The Arduino
    Video · Office Hours: Seoul Korea

    WEEK 6
    Chapter Four: Functions
    This is a relatively short chapter. We will learn about what functions are and how we can use them. The programs in the first chapters of the book are not large enough to require us to develop functions, but as the book moves into more and more complex programs, functions will be an essential way for us to make sense of our code.
    Video · Chapter 4 - Functions
    Quiz · Chapter 4
    Other · Assignment: 4.6
    Video · Interview: Guido van Rossum: The Early Years of Python
    Video · Office Hours: Manila Philippines

    WEEK 7
    Chapter Five: Loops and Iteration
    Loops and iteration complete our four basic programming patterns. Loops are the way we tell Python to do something over and over. Loops are the way we build programs that stay with a problem until the problem is solved.
    Video · Lecture 5.1 Loops and Iteration
    Video · Lecture 5.2 Loop Idioms
    Video · Lecture 5.3 Largest and Smallest
    Quiz · Chapter 5
    Other · Assignment: 5.2
    Video · Worked Exercise: 5.1
    Video · Interview: Guido van Rossum - The Modern Era of Python
    Video · Office Hours: Paris, France
    Reading · Please Rate this Course on Class-Central

  2. COURSE 2

    Python Data Structures

    Current session: May 15 — Jul 10.
    Commitment
    2-4 hours/week
    Subtitles
    English, Chinese (Simplified)

    About the Course

    This course will introduce the core data structures of the Python programming language. We will move past the basics of procedural programming and explore how we can use the Python built-in data structures such as lists, dictionaries, and tuples to perform increasingly complex data analysis. This course will cover Chapters 6-10 of the textbook “Python for Informatics”. This course is equivalent to the second half of the 11-week "Programming for Everybody (Python)" course. This course covers Python 2.
    Show or hide details about course Python Data Structures

    WEEK 1
    Chapter Six: Strings
    In this class, we pick up where we left off in the previous class, starting in Chapter 6 of the textbook and covering Strings and moving into data structures. The second week of this class is dedicated to getting Python installed if you want to actually run the applications on your desktop or laptop. If you choose not to install Python, you can just skip to the third week and get a head start.
    Reading · Reading: Welcome to Python Data Structures
    Video · Video Welcome - Dr. Chuck
    Reading · Textbook
    Video · Fun: The Textbook Authors Meet @PyCon
    Reading · Course Information / Syllabus
    Reading · About the New Platform
    Reading · Submitting Assignments
    Reading · Lecture Slides
    Video · Chapter 6 - Strings
    Quiz · Chapter 6 Quiz
    Other · Assignment 6.5
    Video · Worked Exercise: 6.5
    Video · Bonus: Office Hours New York City
    Video · Bonus: Monash Museum of Computing History
    Reading · Audio Versions of All Lectures
    Reading · Student Curated Course Notes
    Reading · Privacy Policy
    Video · Thanks to all Who Helped Make this Class Possible

    WEEK 2
    Unit: Installing and Using Python
    In this module you will set things up so you can write Python programs. We do not require installation of Python for this class. You can write and test Python programs in the browser using the "Python Code Playground" in this lesson. Please read the "Using Python in this Class" material for details.
    Reading · Important Reading: Using Python in this Class
    Video · Demonstration: Using the Python Playground
    Other · Python Code Playground - Developing Python In the Browser
    Video · Windows 8: Installing Python and Writing A Program
    Video · Windows 8: Taking Screen Shots
    Video · Macintosh: Using Python and Writing A Program
    Video · Macintosh: Taking Screen Shots
    Video · Using Python on a Raspberry Pi / Linux
    Video · Bonus: Eben Upton and the Raspberry Pi
    Practice Peer Review · Optional- Installing Python Screen Shots

    WEEK 3
    Chapter Seven: Files
    Up to now, we have been working with data that is read from the user or data in constants. But real programs process much larger amounts of data by reading and writing files on the secondary storage on your computer. In this chapter we start to write our first programs that read, scan, and process real data.
    Video · Chapter 7 - Files
    Quiz · Chapter 7 Quiz
    Other · Assignment 7.1
    Other · Assignment 7.2
    Reading · Where are the 7.1 and 7.2 worked exercises?
    Video · Demonstration: Worked Exercise 7.6
    Video · Bonus: Office Hours Barcelona
    Video · Bonus: Gordon Bell - Building Blocks of Computing

    WEEK 4
    Chapter Eight: Lists
    As we want to solve more complex problems in Python, we need more powerful variables. Up to now we have been using simple variables to store numbers or strings where we have a single value in a variable. Starting with lists we will store many values in a single variable using an indexing scheme to store, organize, and retrieve different values from within a single variable. We call these multi-valued variables "collections" or "data structures".
    Video · Chapter 8 - Lists
    Video · Fun: Python Lists in Paris
    Quiz · Chapter 8 Quiz
    Other · Assignment 8.4
    Other · Assignment 8.5
    Video · Worked Exercise: Lists
    Video · Bonus: Office Hours - Chicago
    Video · Bonus: Rasmus Lerdorf - Inventing the PHP Language

    WEEK 5
    Chapter Nine: Dictionaries
    The Python dictionary is one of its most powerful data structures. Instead of representing values in a linear list, dictionaries store data as key / value pairs. Using key / value pairs gives us a simple in-memory "database" in a single Python variable.
    Video · Chapter 9 - Dictionaries
    Quiz · Chapter 9 Quiz
    Other · Assignment 9.4
    Video · Worked Exercise: Dictionaries
    Video · Bonus: Office Hours - Amsterdam
    Video · Bonus: Brendan Eich - Inventing Javascript
    Video · Fun: Dr. Chuck Goes Motocross Racing

    WEEK 6
    Chapter Ten: Tuples
    Tuples are our third and final basic Python data structure. Tuples are a simple version of lists. We often use tuples in conjunction with dictionaries to accomplish multi-step tasks like sorting or looping through all of the data in a dictionary.
    Video · Chapter 10 - Tuples
    Quiz · Chapter 10 Quiz
    Other · Assignment 10.2
    Video · Worked Exercise: Tuples and Sorting
    Video · Bonus: Office Hours - Puebla, Mexico
    Video · Bonus: John Resig - Inventing JQuery
    Video · Douglas Crockford: JavaScript Object Notation (JSON)
    Video · Fun: The Greatest Taco in the World

    WEEK 7
    Graduation
    To celebrate your making it to the halfway point in our Python for Everybody Specialization, we welcome you to attend our online graduation ceremony. It is not very long, and it features a Commencement speaker and very short commencement speech.
    Video · Graduation Ceremony
    Reading · Please Rate this Course on Class-Central

  3. COURSE 3

    Using Python to Access Web Data

    Current session: May 15 — Jul 3.
    Commitment
    6 weeks of study, 2-4 hours/week
    Subtitles
    English

    About the Course

    This course will show how one can treat the Internet as a source of data. We will scrape, parse, and read web data as well as access data using web APIs. We will work with HTML, XML, and JSON data formats in Python. This course will cover Chapters 11-13 of the textbook “Python for Informatics”. To succeed in this course, you should be familiar with the material covered in Chapters 1-10 of the textbook and the first two courses in this specialization. These topics include variables and expressions, conditional execution (loops, branching, and try/except), functions, Python data structures (strings, lists, dictionaries, and tuples), and manipulating files. This course covers Python 2.
    Show or hide details about course Using Python to Access Web Data

    WEEK 1
    Getting Started
    In this section you will install Python and a text editor. In previous classes in the specialization this was an optional assignment, but in this class it is the first requirement to get started. From this point forward we will stop using the browser-based Python grading environment because the browser-based Python environment (Skulpt) is not capable of running the more complex programs we will be developing in this class.
    Video · Welcome to The Course
    Reading · Python Textbook
    Reading · Lecture Slides
    Reading · Privacy Policy
    Reading · Syllabus
    Video · Welcome to Python - Guido van Rossum
    Reading · Notes on Python 2.x versus Python 3.x
    Reading · Notes on Choice of Text Editor
    Other · Peer Review: Installing and Running Python Screen Shots
    Video · Windows 8: Installing Python and Writing A Program
    Video · Windows 8: Taking Screen Shots
    Video · Macintosh: Using Python and Writing A Program
    Video · Macintosh: Taking Screen Shots
    Video · Using Python on a Raspberry Pi / Linux
    Video · Windows Vista: Installing Python and Writing A Program
    Video · Windows Vista: Taking Screen Shots

    WEEK 2
    Regular Expressions (Chapter 11)
    Regular expressions are a very specialized language that allow us to succinctly search strings and extract data from strings. Regular expressions are a language unto themselves. It is not essential to know how to use regular expressions, but they can be quite useful and powerful.
    Video · Regular Expressions - Part 1
    Video · Regular Expressions - Part 2
    Reading · Python Regular Expression Quick Guide
    Quiz · Quiz: Regular Expressions
    Other · Extracting Data With Regular Expressions
    Video · Bonus: Office Hours - Den Haag
    Video · Bonus Interview: Bjarne Stroustrup - C++

    WEEK 3
    Networks and Sockets (Chapter 12)
    In this section we learn about the protocols that web browsers use to retrieve documents and web applications use to interact with Application Program Interfaces (APIs).
    Video · Networked Programs
    Video · From Sockets to Applications
    Video · Let’s Write a Web Browser
    Reading · If You Want to Learn More
    Quiz · Networks and Sockets
    Other · Understanding the Request / Response Cycle
    Video · Bonus Video: Leonard Kleinrock - The First Two Packets on the ARPANET
    Video · Bonus Video: Robert Cailliau - co-Inventor of the Web
    Video · Bonus: Office Hours - Atlanta GA (Buckhead)
    Video · Fun: Dr. Chuck @ CNN Reading the News

    WEEK 4
    Programs that Surf the Web (Chapter 12)
    In this section we learn to use Python to retrieve data from web sites and APIs over the Internet.
    Video · Understanding HTML
    Video · Parsing HTML with BeautifulSoup
    Quiz · Reading Web Data From Python
    Reading · Notes Regarding the Use of Beautiful Soup
    Other · Scraping HTML Data with BeautifulSoup
    Other · Assignment: Following Links in HTML Using BeautifulSoup
    Video · Bonus: Office Hours - Montreal
    Video · Bonus Interview: Tim Berners-Lee - Inventing the Web
    Video · Fun: I Got My Mojo Working - Geneva, Switzerland

    WEEK 5
    Web Services and XML (Chapter 13)
    In this section, we learn how to retrieve and parse XML (eXtensible Markup Language) data.
    Video · Web Services Overview
    Video · Interview: Roy Fielding - Understanding the REST Architecture
    Video · eXtensible Markup Language - XML
    Video · XML Schema
    Video · Parsing XML in Python
    Quiz · eXtensible Markup Language
    Other · Extracting Data from XML
    Video · Bonus: Office Hours - Boston
    Video · Bonus Video: Ian Horrocks / RDF / OWL (Advanced)

    WEEK 6
    JSON and the REST Architecture (Chapter 13)
    In this module, we work with Application Program Interfaces / Web Services using the JavaScript Object Notation (JSON) data format.
    Video · JavaScript Object Notation
    Video · Interview: Douglas Crockford - Discovering JSON
    Video · Service Oriented Approach
    Video · Video: Service Oriented Architectures
    Video · Accessing APIs in Python
    Video · API Security and Rate Limiting
    Quiz · REST, JSON, and APIs
    Other · Extracting Data from JSON
    Other · Using the GeoJSON API
    Video · Bonus: Office Hours - Melbourne, AU
    Video · Bonus: Office Hours - Santa Monica, CA
    Video · Bonus: Class Reunion at Bletchley Park
    Reading · Please Rate this Course on Class-Central

  4. COURSE 4

    Using Databases with Python

    Current session: May 15 — Jun 26.
    Commitment
    5 weeks of study, 2-3 hours/week
    Subtitles
    English

    About the Course

    This course will introduce students to the basics of the Structured Query Language (SQL) as well as basic database design for storing data as part of a multi-step data gathering, analysis, and processing effort. The course will use SQLite3 as its database. We will also build web crawlers and multi-step data gathering and visualization processes. We will use the D3.js library to do basic data visualization. This course will cover Chapters 14-15 of the book “Python for Informatics”. To succeed in this course, you should be familiar with the material covered in Chapters 1-13 of the textbook and the first three courses in this specialization. This course covers Python 2.
    Show or hide details about course Using Databases with Python

    WEEK 1
    Object Oriented Python
    To start this class out we cover the basics of Object Oriented Python. We won't be writing our own objects, but since many of the things we use like BeautifulSoup, strings, dictionaries, database connections all use Object Oriented (OO) patterns we should at least understand some of its patterns and terminology.
    Video · Welcome to Using Databases with Python
    Reading · Python Textbook
    Reading · Lecture Slides
    Reading · Privacy Policy
    Reading · Syllabus
    Video · Introduction
    Video · What is an "Object"?
    Video · Terminology
    Video · Simple Python Objects
    Video · Object Lifecycle
    Video · Inheritance
    Quiz · Object Oriented Programming
    Video · Bonus: Interview - Software Engineering - Bertrand Meyer
    Video · Bonus: Office Hours - London

    WEEK 2
    Basic Structured Query Language
    We learn the four core CRUD operations (Create, Read, Update, and Delete) to manage data stored in a database.
    Video · Database Introduction
    Video · Using Databases
    Video · Single Table CRUD
    Video · Email Database Demo
    Quiz · Single-Table SQL
    Other · Our First Database
    Other · Counting Email in a Database
    Video · Bonus: Office Hours Zagreb, Croatia
    Video · Interview: Elizabeth Fong - The Early Years of SQL

    WEEK 3
    Data Models and Relational SQL
    In this section we learn about how data is stored across multiple tables in a database and how rows are linked (i.e., we establish relationships) in the database.
    Video · Designing a Data Model
    Video · Representing a Data Model in Tables
    Video · Inserting Relational Data
    Video · Reconstructing data with JOIN
    Quiz · Multi-Table Relational SQL
    Video · Multi-table Tracks Demo
    Other · Multi-Table Database - Tracks
    Video · Bonus: Office Hours Perth, Australia
    Video · Bonus Interview: Niklaus Wirth
    Video · Bonus: Office Hours Barcelona

    WEEK 4
    Many-to-Many Relationships in SQL
    In this section we explore how to model situations like students enrolling in courses where each course has many students and each student is enrolled in many courses.
    Video · Many-to-Many Relationships
    Video · Many-to-Many Roster Demo
    Quiz · Many-to-Many Relationships and Python
    Other · Many Students in Many Courses
    Video · Bonus: Office Hours Mexico, City
    Video · Bonus Interview: Andrew Tannenbaum - Minix

    WEEK 5
    Databases and Visualization
    In this section, we put it all together, retrieve and process some data and then use the Google Maps API to visualize our data.
    Video · Geocoding
    Video · Page Rank and Web Searching
    Video · Gmane - Mailing Lists
    Video · GeoCoding API Demo
    Other · Databases and Visualization (peer-graded)
    Video · Bonus: Office Hours - Amsterdam
    Video · Bonus Interview: Richard Stallman - Free Software Foundation
    Video · Bonus Interview: Brian Behlendorf - Apache Foundation
    Reading · Please Rate this Course on Class-Central

  5. COURSE 5

    Capstone: Retrieving, Processing, and Visualizing Data with Python

    Upcoming session: Jun 26 — Aug 21.
    Commitment
    6 weeks of study, 2-4 hours/week
    Subtitles
    English

    About the Capstone Project

    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. Chapter 15 from the book “Python for Informatics” will serve as the backbone for the capstone. This course covers Python 2.
    Show or hide details about course Capstone: Retrieving, Processing, and Visualizing Data with Python

    WEEK 1
    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.
    Video · Introduction: Welcome to the Class
    Reading · Capstone Overview
    Video · Office Hours in Den Haag, Netherlands
    Video · Interview: John Resig and Pam Fox - Khan Academy

    WEEK 2
    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 15 of the textbook.
    Reading · Building a Search Engine - Introduction
    Video · Page Rank Introduction
    Video · Page Rank Spidering
    Video · Computing Page Rank
    Video · Page Rank - Visualization
    Other · Peer Grade: Page Rank
    Video · Office Hours Detroit, Michigan
    Video · Interview: Anil Jain - Image Processing

    WEEK 3
    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.
    Reading · Identifying Your Data Source - Introduction
    Reading · List of Data Sources (Instructional Staff Curated)
    Other · Identifying a Data Source
    Video · Dr. Chuck's New Kitten - Sakaiger
    Video · Interview: Bruce Schneier - The Security Mindset

    WEEK 4
    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.
    Reading · Spidering and Modeling Email Data - Introduction
    Video · Gmane Introduction
    Video · Gmane Loading from the Web
    Video · Gmane Data Cleanup/Modeling
    Video · Gmane Looking at Modeled Data
    Other · Loading and Modeling Mail Data
    Video · Office Hours Baltimore, MD
    Video · Interview: Bruce Schneier - Building Cryptographic Systems

    WEEK 5
    Accessing New Data Sources (Project)
    The task for this week is to make a discussion thread post that reflects the progress you have made to date in retrieving and cleaning up your data source so can perform your analysis. Feedback from other students is encouraged to help you refine the process.
    Reading · Accessing New Data Sources - Introduction
    Other · Analyzing a Data Source
    Video · Office Hours: Dr. Chuck Pretends to be Anthony Bourdain

    WEEK 6
    Visualizing Email Data
    In the final required assignment, we will do two visualizations of the email data you have retrieved and processed: a word cloud to visualize the frequency distribution and a timeline to show how the data is changing over time.
    Reading · Visualizing Email Data
    Video · Gmane Basic Statistics and Word Cloud
    Video · Gmane Visualizing Lines
    Other · Visualizing Email Data
    Video · Office Hours, Montreal, Canada
    Video · Interview: Nathaniel Borenstein - The Father of MIME

    WEEK 7
    Visualizing new Data Sources (Project)
    This week you will discuss the analysis of your data to the class. While many of the projects will result in a visualization of the data, any other results of analyzing the data are equally valued, so use whatever form of analysis and display is most appropriate to the data set you have selected.
    Reading · Visualizing new Data Sources - Introduction
    Other · Data Analysis and Visualization
    Video · Office Hours - Dr. Chuck's Office - Ann Arbor, Michigan
    Video · Video: Steve Jobs, NeXT and the Internet

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The University of Michigan is recognized as a leader in higher education due to the outstanding quality of its 19 schools and colleges, internationally recognized faculty, and departments with 250 degree programs.
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.

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