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NOTE: The course schedule below does not match exactly the content in the Jupyter Notebook

References

CS50's Introduction to Programming with Python (harvard.edu)

Python Basics: Introduction to Python (Learning Path) – Real Python

About this course - Python Programming MOOC 2023

futurecoder: learn python from scratch

Learn Python with Jupyter

PhilipYip1988/python-tutorials: JupyterLab based Python Tutorials. These are detailed markdown tutorials covering installation, markdown, text datatypes, numeric data types, collections, programming constructs, the collections, itertools, math, random, datetime, statistics, sys, operating system, abc, csv and pickle modules, the numpy, pandas and matplotlib libraries. (github.com)

Python SpeedSheet

Online Python Tutor - visualize, debug, get AI help for Python, Java, C, C++, and JavaScript

jackfrued/Python-100-Days: Python - 100天从新手到大师 (github.com)

The Python Tutorial — Python 3.12.2 documentation

Course Schedule (15 Courses, 2 hours)

Session 1: Introduction to Python and Courses

  • Course Overview
  • Overview of Python and Its Applications
  • Installing Python and Setting Up the Development Environment
  • Running Python Scripts and Using the Interactive Shell
  • print() function
  • Basic Syntax, Comments, and Indentation

Session 2: Variables and assignments, data types and input

  • Variables and assignments
  • Numeric data types (int, float)
  • String data type (basic)
  • input() function
  • Type conversion

Session 3: Control Flow - Conditional Statements

  • Boolean data type and its operators
  • If, Elif, and Else Statements
  • Nested conditional statements
  • Ternary operator

Session 4: Data Structures - Lists

  • Creating and Accessing Lists
  • List Methods and Operations
  • Slicing Lists
  • List Comprehensions

Session 5: Control Flow - Loops

  • While Loops
  • For Loops
  • Break, Continue, and Pass Statements
  • Nested Loops

Session 6: Functions

  • Defining and calling functions
  • Parameters and arguments
  • Return values
  • Scope of variables
  • Lambda Functions

Session 7: Data Structures - Tuples and Sets

  • Creating and Accessing Tuples
  • Tuple Methods and Operations
  • Creating and Manipulating Sets
  • Set Operations (Union, Intersection, Difference)

Session 8: Data Structures - Dictionaries (Including Defaultdict)

  • Creating and Accessing Dictionaries
  • Dictionary Methods and Operations
  • Iterating Over Dictionaries
  • Nested Dictionaries

Session 9: Strings and String Manipulation

  • String Methods and Operations
  • Formatting Strings
  • Regular Expressions

Session 10: File Handling and Exception Handling

  • Opening and Closing Files
  • Reading from and Writing to Files
  • With Statement
  • Handling Exceptions with Try, Except, and Finally
  • Raising Exceptions
  • Reading from CSV files

Session 11: Numpy and Matplotlib

Session 12: Object-Oriented Programming (OOP) Basics

  • Classes and Objects
  • Attributes and Methods
  • Constructors
  • Inheritance

Session 13: Advanced OOP Concepts and and additional techniques

  • Abstract Classes and Interfaces
  • Operator Overloading
  • Decorators
  • Generators and Iterators

Session 14: Recursion

  • Introduction to Recursion
  • Recursive Functions
  • Memoization

Session 15: Final Project

  • Project Assignment and Work
  • Review of Key Concepts
  • Q&A and Problem-Solving Session