Python Programming Course (Self-Paced Professional Training)

The Python Programming Course – Beginner to Intermediate is a comprehensive, practice-focused program designed for students, professionals, and career switchers who want to build a strong foundation in Python and apply it to real-world problem solving and data analysis.

The course begins with Python fundamentals, including environment setup using Anaconda, Jupyter Notebook, and Google Colab. You will learn variables, data types, operators, and basic syntax while gaining confidence in writing and executing Python code.

As you progress, the course dives deep into core Python concepts such as lists, tuples, sets, dictionaries, conditional statements, loops, and functions. These topics are reinforced with practical examples and mini use cases to strengthen logical thinking and coding structure.

In the intermediate phase, the course focuses on file handling, data manipulation, and analysis. You will work with Pandas and NumPy to clean datasets, handle missing values, manipulate arrays, and perform basic statistical analysis. The curriculum also includes data visualization using Matplotlib and Seaborn, enabling you to create meaningful charts, graphs, and 3D visualizations.

By the end of this course, learners will have the confidence to write clean Python code, work with real datasets, visualize insights, and move forward into advanced domains such as Data Science, Machine Learning, Automation, or Backend Development.

This course is ideal for anyone seeking a beginner-to-intermediate Python certification with practical, industry-relevant skills.

What You Will Learn (Session Highlights)

Python Fundamentals

• Python features and real-world applications

• Environment setup with Anaconda, Jupyter, and Colab

• Variables, data types, and basic operations

Core Python Programming

• Lists, tuples, sets, and dictionaries

• Conditional statements and user input handling

• Loops (for, while) and control statements

• Writing reusable functions

File Handling & Data Processing

• Reading, writing, appending, and deleting files

• Working with CSV and JSON files

• Handling missing and duplicate data

Data Analysis & Visualization

• Pandas Series and DataFrames

• NumPy arrays and indexing

• Data cleaning and transformation

• Data visualization using Matplotlib and Seaborn

• Statistical analysis and 3D plotting

Learning Outcomes

After completing this course, you will be able to:

• Set up and use Python development environments

• Write structured and efficient Python programs

• Work with core Python data structures

• Handle files and real-world datasets

• Clean and analyze data using Pandas and NumPy

• Visualize data using professional charts and plots

• Build a strong foundation for advanced Python careers