End to End Case Study
1. Introduction to Python
What you’ll learn
- Introduction to Python.
- Python Libraries.
- Introduction to Python Programming.
- Data Structures and Functions in Python.
- Working with Libraries and Handling Files.
- Python Introduction to NumPy.
Course Content
- Introduction to Python –> 1 lecture • 38min.
- Python Libraries –> 1 lecture • 26min.
- Introduction to Python Programming –> 1 lecture • 35min.
- Introduction to Python Programming Part2 –> 1 lecture • 33min.
- Data Structures and Functions in Python –> 1 lecture • 24min.
- Data Structures and Functions in Python Part2 –> 1 lecture • 36min.
- Working with Libraries and Handling Files –> 1 lecture • 27min.
- Python Introduction to Numpy –> 1 lecture • 26min.
Requirements
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.
Courtesy,
Dr. FAK Noble Ai Researcher, Scientists, Product Developer, Innovator & Pure Consciousness Expert