Python Programming Fundamentals – Online Course

Course Description

1. Introduction to Python

Overview:

This section introduces the Python programming language, its history, and its importance in the programming world.

Topics Covered:

What is Python?

Python’s History and Evolution

Why Choose Python? (Features and Advantages)

Setting Up the Python Environment (Installation of Python, IDEs, and Editors)

Writing and Executing Your First Python Program

Learning Outcomes:

Understand the basics of Python and its applications.

Set up Python on your computer and run simple programs.

2. Python Libraries

Overview:

Explore the vast ecosystem of Python libraries and how they extend the capabilities of Python.

Topics Covered:

Introduction to Python Libraries and Modules

Standard Library vs. Third-Party Libraries

Installing and Managing Libraries using pip

Overview of Popular Libraries: NumPy, Pandas, Matplotlib, etc.

Learning Outcomes:

Understand what libraries are and how to use them.

Learn how to install and manage Python libraries.

3. Introduction to Python Programming

Overview:

Dive into the core syntax and programming constructs of Python.

Topics Covered:

Python Syntax and Semantics

Variables, Data Types (Numbers, Strings, Booleans)

Operators and Expressions

Basic Input and Output

Commenting and Writing Clean Code

Learning Outcomes:

Write basic Python programs using variables and data types.

Perform arithmetic operations and handle user input.

4. Introduction to Python Programming (Part 2)

Overview:

Build on the basics by exploring control flow and loops.

Topics Covered:

Control Flow: Conditional Statements (if, else, elif)

Loops: for and while Loops

Introduction to Iterables and Iterators

Break and Continue Statements

Learning Outcomes:

Implement decision-making in code using conditionals.

Use loops to iterate over data and perform repetitive tasks.

5. Data Structures and Functions in Python

Overview:

Learn about essential data structures and how to create reusable code with functions.

Topics Covered:

Lists, Tuples, and Sets

Dictionaries: Key-Value Pairs

Defining and Using Functions

Function Parameters and Return Values

Scope and Lifetime of Variables

Learning Outcomes:

Store and manipulate data using lists, tuples, and dictionaries.

Write functions to create modular, reusable code.

6. Data Structures and Functions in Python (Part 2)

Overview:

Continue exploring data structures and more advanced function concepts.

Topics Covered:

Advanced List Operations (Slicing, List Comprehensions)

Working with Nested Data Structures

Anonymous Functions (Lambda Expressions)

Higher-Order Functions (map, filter, reduce)

Error Handling and Exceptions in Functions

Learning Outcomes:

Perform complex operations on data structures.

Handle errors gracefully and write more sophisticated functions.

7. Working with Libraries and Handling Files

Overview:

Learn how to work with Python libraries and manage file operations.

Topics Covered:

Importing and Using Libraries

File Handling: Reading and Writing Files

Working with CSV Files using the csv module

Introduction to Context Managers

Best Practices for File Operations

Learning Outcomes:

Read from and write to files using Python.

Use libraries to enhance Python’s functionality.

8. Python Introduction to NumPy

Overview:

Get introduced to NumPy, a powerful library for numerical computing.

Topics Covered:

What is NumPy and Why Use It?

Creating and Manipulating Arrays

Basic Array Operations

Working with Multi-dimensional Arrays

Array Indexing and Slicing

Basic Mathematical Functions with NumPy

Learning Outcomes:

Use NumPy to work with large datasets efficiently.

Perform mathematical operations on arrays and matrices.

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Dr. FAK Noble Ai Researcher, Scientists, Product Developer, Innovator & Pure Consciousness Expert