Python Programming

Purpose
This course is designed to introduce learners to Python programming, covering fundamental concepts, data structures, and advanced features. The course bridges theory with hands-on coding experience, preparing learners to build real-world applications using Python.

Cost:

Prerequisites

• Basic understanding of programming concepts (recommended but not mandatory)
• Modest computer skills
• Access to a computer with Python installed (or access to an online compiler)
• Active Zoom® account

Topics

1. Introduction to Python and Development Environment (2 hours)

• Introduction to Python and its applications
• Installing Python and setting up an IDE (PyCharm, VS Code, or Jupyter Notebook)
• Running Python scripts

2. Python Basics (2 hours)

• Variables and data types
• Operators and expressions
• Type conversions

3. Control Flow Statements (2 hours)

• Conditional statements (if, elif, else)
• Loops (for, while)
• Break, continue, and pass statements

4. Functions and Modules (2 hours)

• Defining and calling functions
• Function arguments and return values
• Creating and using modules

5. Data Structures in Python (2 hours)

• Lists and tuples
• Dictionaries and sets
• List comprehensions

6. File Handling (2 hours)

• Reading and writing files
• Working with CSV and JSON files
• Exception handling

7. Object-Oriented Programming (2 hours)

• Classes and objects
• Inheritance and polymorphism
• Encapsulation and abstraction

8. Working with Databases (2 hours)

• Introduction to SQLite and MySQL
• Connecting Python to a database
• Performing CRUD operations

9. Web Scraping and APIs (2 hours)

• Introduction to web scraping with BeautifulSoup
• Making HTTP requests with requests
• Working with REST APIs

10. Data Analysis with Python (2 hours)

• Using Pandas for data manipulation
• Visualization with Matplotlib and Seaborn
• Basic statistics with NumPy

11. Introduction to Machine Learning (2 hours)

• Basics of Machine Learning
• Using Scikit-learn for simple ML models
• Supervised vs. Unsupervised learning

12. Capstone Project (3 hours)

• Building a Python-based project
• Applying the concepts learned in the course
• Presenting and submitting the final project

Deliverables

• Write Python scripts to automate tasks and process data.
• Develop Python programs using functions, OOP, and databases.
• Work with APIs and web scraping tools.
• Perform data analysis and visualization.
• Submit a final project report.

Certificate of Completion