Python Programming

1. Course Overview

The Python Programming training programe provides learners with foundational to intermediate skills in Python, enabling them to build applications, automate tasks, analyze data, and develop problem-solving techniques. This program is highly practical with hands-on exercises, real-world projects, and progressive skill building.

It prepares students for careers in software development, data analysis, automation, and further learning in AI/ML.

2. Target Audience

• Beginners with little or no programming background
• Students preparing for IT/software careers
• Working professionals entering software development or data analytics
• Individuals preparing for advanced Python certifications

3. Course Duration

Duration: 2–4 Months

• Instructor-led sessions: 60–80 hours
• Hands-on coding labs: 60+ hours
• Assessments & final project included

4. Learning Outcomes

By the end of this program, learners will be able to:

• Use Python syntax, data structures, and control flow
• Write functional programs using functions and modules
• Work with files, exceptions, and standard libraries
• Build applications using OOP (Object-Oriented Programming)
• Use Python for automation tasks
• Perform data manipulation and visualization
• Use Python with databases and APIs
• Develop and deploy Python projects
• Understand best practices for debugging and testing

5. Course Structure & Modules

Module 1: Introduction to Python

Topics:

• What is Python and where it is used
• Installing Python & working with IDEs (VS Code, PyCharm)
• Running Python scripts
• Understanding syntax, indentation, comments

Skills: Basic environment setup and Python execution.

Module 2: Python Basics

Topics:

• Variables and data types
• Operators
• Type conversion
• Input/Output functions

Skills: Foundational Python programming concepts.

Module 3: Control Flow

Topics:

• Conditional statements (if, elif, else)
• Loops (for, while)
• Loop control (break, continue, pass)

Skills: Writing logical and structured code.

Module 4: Data Structures

Topics:

• Strings
• Lists
• Tuples
• Dictionaries
• Sets
• Common methods and operations

Skills: Efficient data storage and processing.

Module 5: Functions & Modules

Topics:

• Defining and calling functions
• Arguments and return values
• Lambda functions
• Creating and importing modules
• Using Python standard libraries

Skills: Modular and reusable code development.

Module 6: File Handling & Exception Management

Topics:

• Reading and writing files
• Working with JSON
• Exception types
• try/except/else/finally
• Custom exceptions

Skills: Interacting with external data and robust error handling.

Module 7: Object-Oriented Programming (OOP)

Topics:

• Classes and objects
• Attributes and methods
• Constructors
• Inheritance
• Polymorphism
• Encapsulation
• Abstraction

Skills: Designing structured applications with OOP.

Module 8: Working With External Data

Topics:

• APIs and HTTP requests
• Using JSON data
• Web scraping basics (requests, BeautifulSoup)
• Intro to databases
• Using SQLite/MySQL with Python

Skills: Interacting with online services and databases.

Module 9: Automation & Scripting

Topics:

• Automating daily tasks
• Working with OS module
• Scheduling scripts
• Writing CLI utilities

Skills: Using Python to automate workflows.

Module 10: Data Analysis With Python (Intro)

Topics:

• NumPy basics
• Pandas for data manipulation
• Matplotlib for visualization
• Working with datasets

Skills: Foundational data analysis and data visualization.

Module 11: Testing, Debugging & Best Practices

Topics:

• Debugging techniques
• Unit testing with unittest/pytest
• Code style (PEP 8)
• Virtual environments
• Using pip and managing packages

Skills: Writing high-quality, maintainable code.

Module 12: Final Project

Learners develop and present a functional Python application.

Examples:

• Data analysis dashboard
• CLI password manager
• Automation tool for file management
• Web scraper that stores data in a database
• Simple API-based application (e.g., weather app)

6. Assessment Methods

• Module quizzes
• Coding challenges
• Practical assignments
• Mid-term programming task
• Final capstone project

7. Certifications Prepared For

While not directly tied to one exam, the course prepares learners for:

• PCAP – Certified Associate in Python Programming
• CompTIA Python+ (future role-based certifications)
• PCEP – Certified Entry-Level Python Programmer

8. Career Opportunities

Graduates may qualify for roles such as:

• Junior Python Developer
• Data Analyst (entry-level)
• Automation Technician
• QA/Test Automation Assistant
• Backend Developer (entry-level)
• IT Support Scripter