Python for Everybody - Full University Python Course

Embark on a comprehensive 14-hour university-level Python 3 course designed for beginners with no prior programming experience. Learn the fundamentals of computer programming using Python, covering topics from basic syntax to advanced concepts like web services and data visualization. Explore hardware architecture, installation processes, variables, conditional execution, functions, loops, file handling, data structures, regular expressions, networking, databases, and object-oriented programming. Gain hands-on experience through numerous code examples and projects, including web scraping, API usage, and data analysis. Access free supplementary materials such as sample code, lecture slides, and a textbook to enhance your learning experience. Taught by Dr. Charles Severance, a Clinical Professor at the University of Michigan School of Information, this course provides a solid foundation for aspiring programmers and data enthusiasts.

Why Program?.
Why Program? - Hardware Architecture.
Python 3 Windows Installation.
Python 3 Mac Installation.
Why Program? - Python as a Language.
Why Program? - What do we say?.
Variables, Expressions, and Statements.
Variables, Expressions, and Statements - Expressions.
Conditional Execution.
Conditional Execution - More Conditional Structures.
Functions.
Functions - Functions of our own.
Loops and Iteration.
Loops and Iteration - Definite Loops.
Loops and Iteration - Loop Idioms.
Loops and Iteration - More Loop Patterns.
Strings.
Strings - More String Operations.
Reading Files.
Reading Files - Reading Files in Python.
Python Lists.
Python Lists - Loop Operations.
Python Lists - Strings vs. Lists.
Python Lists - Strings, Files, Lists & the Guardian Pattern.
Dictionaries.
Dictionaries - Counting.
Dictionaries - Counting Words in Text.
Dictionaries - Counting Word Frequency Using a Dictionary.
Tuples.
Tuples - Sorting.
Tuples - Sorting a Dictionary Using Tuples.
Regular Expressions.
Regular Expressions - From Matching to Extracting.
Regular Expressions - String Parsing.
Networked Programs.
Networked Programs - Application Protocols.
Networked Programs - Write a Web Browser.
Networked Programs - Code Example: socket1.py.
Networked Programs - Characters and Strings.
Networked Programs - urllib.
Networked Programs - Code Example: urllib1.py, urlwords.py.
Networked Programs - Parsing HTML.
Networked Programs - Code Example: urllinks.py.
Using Web Services.
Using Web Services - XML.
Using Web Services - Code Example: xml1.py, xml2.py.
Using Web Services - XML Schema.
Using Web Services - JavaScipt Notation.
Using Web Services - Code Example: json1.py, json2.py.
Using Web Services - Service Oriented Approach.
Using Web Services - Web Services.
Using Web Services - Code Example: geojson.py.
Using Web Services - API Security & Rate Limiting.
Using Web Services - Code Example: twitter1.py, twitter2.py.
Python Objects.
Python Objects - Sample Code.
Python Objects - Object Lifecycle.
Python Objects - Inheritance.
Databases.
Databases - SQLite Browser.
Databases - Code Sample: emaildb.py.
Databases - Code Sample: twspider.py.
Databases - Database Design.
Databases - Representing Relationships.
Databases - Relationship Building.
Databases - Join Operation.
Databases - Code Sample: tracks.py.
Databases - Many-to-Many Relationships.
Databases - Code Sample: roster.py.
Databases - Code Sample: twspider.py.
Data Visualization.
Data Visualization - Code Sample: Geodata.
Data Visualization - Page Rank.
Data Visualization - Code Sample: Pagerank Spidering.
Data Visualization - Code Sample: Pagerank Computation.
Data Visualization - Code Sample: Pagerank Visualization.
Data Visualization - Mailing List Crawl.
Data Visualization - Code Sample: Gmane Data Retrieval.
Data Visualization - Code Sample: Gmane Data Modeling.
Data Visualization - Code Sample: Gmane Data Visualization.