Python Programming Roadmap

Course Objective:

• Learn the fundamentals of the Python programming language.
• Understand basic and advanced programming concepts.
• Develop skills to write efficient and scalable Python code.
• Gain proficiency in using Python for various applications, including web development, data analysis, and automation.

1

Introduction to Python:

• History and features of Python .
• Setting up the development environment.
• Basic syntax and structure of Python programs.

2

Data Types and Variables:

• Fundamental data types (int, float, str, list, dict, etc.).
• Declaring and initializing variables.
• Type conversion and casting.

3

Control Structures:

• Conditional statements (if, elif, else).
• Looping constructs (for, while, do-while).
• Comprehensions and generators.

4

Functions and Modules:

• Defining and calling functions.
• Lambda functions and higher-order functions.
• Creating and using modules and packages.

5

Object-Oriented Programming:

• Classes and objects.
• Inheritance, polymorphism, and encapsulation.
• Special methods and properties.

6

File Handling:

• Reading from and writing to files.
• Working with different file formats (text, CSV, JSON).
• Context managers and file operations.

7

Exception Handling:

• Handling errors and exceptions.
• Try, except, else, and finally blocks.
• Creating custom exceptions.

8

Libraries and Frameworks:

• Popular Python libraries (NumPy, Pandas, Matplotlib).
• Web frameworks (Django, Flask).
• Automation tools (Selenium, Beautiful Soup).

9

Data Analysis and Visualization:

• Working with data using Pandas.
• Visualizing data with Matplotlib and Seaborn.
• Performing data analysis and generating reports.

10

Project Work:

• Hands-on projects to apply learned concepts.
• Developing real-world applications.
• Testing and debugging code.

Skills You'll Gain:

• Proficiency in Python programming language.
• Understanding of both basic and advanced programming concepts.
• Ability to build and deploy Python applications.
• Experience with data analysis and visualization.

Duration:

Typically ranges from 4 to 7 weeks, depending on the course intensity and format.

Certification:

Earn a certificate of completion that can be added to your resume or LinkedIn profile.