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Hinata Hyuga
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Web Development
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Python (Basic to Advance)

Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book.

Overview

  • Timing --:--:--
  • Lectures 44
  • Quizzes 8
  • Assignments 8
  • Duration 2 Month
  • Skill level Beginners
Course Description

Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Its high-level built-in data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development, as well as for use as a scripting or glue language to connect existing components together. Python's simple, easy-to-learn syntax emphasizes readability and therefore reduces the cost of program maintenance. Python supports modules and packages, which encourages program modularity and code reuse. The Python interpreter and the extensive standard library are available in source or binary form without charge for all major platforms and can be freely distributed.

Often, programmers fall in love with Python because of the increased productivity it provides. Since there is no compilation step, the edit-test-debug cycle is incredibly fast. Debugging Python programs is easy: a bug or bad input will never cause a segmentation fault. Instead, when the interpreter discovers an error, it raises an exception. When the program doesn't catch the exception, the interpreter prints a stack trace. A source-level debugger allows inspection of local and global variables, evaluation of arbitrary expressions, setting breakpoints, stepping through the code a line at a time, and so on. The debugger is written in Python itself, testifying to Python's introspective power. On the other hand, often the quickest way to debug a program is to add a few print statements to the source: the fast edit-test-debug cycle makes this simple approach very effective.

Curriculum


Vital Python – Math, Strings, Conditionals, and Loops
Vital Python
Numbers: Operations, Types, and Variables
To Open a Jupyter Notebook
Python as a Calculator
Standard Math Operations
Basic Math Operations
Order of Operations
Spacing in Python
Number Types: Integers and Floats
Complex Number Types
Errors in Python

Variables
Variable Assignment
Changing Types
Reassigning Variables in Terms of Themselves
Variable Names
Multiple Variables
Comments
Docstrings
Theorem in Python

Strings: Concatenation, Methods, and input()
String Syntax
Escape Sequences with Quotes
Multi-Line Strings
The print() Function
String Operations and Concatenation
String Interpolation
Comma Separators
Format
The len() Function
String Methods
Casting
The input() Function
String Indexing and Slicing
Indexing
Slicing

Strings and Their Methods
Booleans and Conditionals
Booleans
Logical Operators
Comparison Operators
Comparing Strings
Conditionals
The if Syntax
Indentation
if else
The elif Statement
Loops
The while Loops
An Infinite Loop
break
Programs
The for Loop
The continue Keyword

Python Structures
The Power of Lists
List Methods
Accessing an Item from a List
Adding an Item to a List
Dictionary Keys and Values
a List and a Dictionary
Zipping and Unzipping Dictionaries Using zip()
Dictionary Methods
Tuples
A Survey of Sets
Set Operations
Choosing Types

Executing Python – Programs
Algorithms, and Functions
Introduction
Python Scripts and Modules
Shebangs in Ubuntu
Docstrings
Imports
The if __name__ == "__main__" Statement
Basic Functions
Positional Arguments
Keyword Arguments
Iterative Functions
Exiting Early
Activity 10: The Fibonacci Function with an Iteration
Helper Functions
Don't Repeat Yourself
Variable Scope
Variables
Defining inside versus outside a Function
The Global Keyword
The Nonlocal Keyword
Lambda Functions
Mapping with Lambda Functions
Filtering with Lambda Functions
Sorting with Lambda Functions

Extending Python, Files, Errors, and Graphs
Reading Files
Writing Files
the Date and Time in a Text File

  • First Level
    • Lesson 1. Introduction to UI Design
      120 minutes
    • Lesson 2. User Research and Design
      60 minutes
    • Lesson 3. Evaluating User Interfaces Part 1
      85 minutes
  • Second Level
    • Lesson 1. Prototyping and Design
      110 minutes
    • Lesson 2. UI Design Capstone
      120 minutes
    • Lesson 3. Evaluating User Interfaces Part 2
      120 minutes
  • Final
    • Part 1. Final Test
      120 minutes
    • Part 2. Online Test
      120 minutes

Instructor

Keny White
Professor

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