This Python course is structured to take learners from the basics of programming to intermediate-level applications. It begins with an introduction to Python syntax, data types, and operators before moving into conditional statements, loops, and string manipulation. Learners will work with lists, tuples, sets, and dictionaries to manage data efficiently. The course also explores built-in modules, file handling, and functions to help structure code better. Additionally, students will gain exposure to AI-based computer vision, data visualization, and machine learning fundamentals using Python. Through hands-on exercises and projects like password validation, number guessing games, and data analysis, learners will gain practical coding experience and problem-solving expertise.

Key Benefits:

Live, interactive sessions with expert instructors.
Hands-on coding exercises and real-world projects.
Step-by-step guidance from Python fundamentals to intermediate applications.
Exposure to AI, data visualization, and predictive modeling.
Builds problem-solving and logical thinking skills for future programming success.

What You’ll Learn:

Python Basics & Control Structures

Setting up Python and choosing an IDE.
Understanding variables, operators, and expressions.
Using conditional statements (if-else, nested-if) and loops (for, while).

Data Types & String Manipulation

Working with lists, tuples, sets, and dictionaries.
Performing indexing, slicing, and string operations.
Implementing data type conversions and built-in functions.

Functions & File Handling

Writing and using user-defined functions.
Understanding function arguments and return values.
Reading and writing files, renaming files, and working with binary data.

Advanced Python Concepts

Importing and using modules like math, random, and datetime.
Introduction to AI-based image processing and object detection.
Data visualization using Plotly and Pandas.

Projects & Hands-on Learning

Developing interactive applications like a Rock-Paper-Scissors game.
Creating AI-based projects like virtual keyboard and gesture control.
Implementing machine learning models for data analysis and predictions.