Intro to Python

Learn Python programming from the ground up with a focus on data analysis and business applications. Master variables, control flow, functions, and data structures required for data science.

Course Structure

Module 1: Python Foundations

1.1 Object-Oriented Programming - Introduction to classes, objects, and OOP concepts
1.2 Variables and Data Types - Data types, variables, and basic operations
1.3 Control Flow - If statements, loops, and program logic
1.4 Functions - Creating and using functions for code organization

Module 2: Data Structures

2.1 Lists - Working with lists, indexing, and list methods
2.2 Dictionaries - Key-value pairs and dictionary operations
2.3 Tuples - Immutable data structures and their applications

Module 3: Applications

3.1 File Handling - Reading and writing files, CSV processing
3.2 Error Handling & Debugging - Exception handling, logging, and debugging techniques
3.3 Libraries & Imports - Python libraries and data science tools

Prerequisites

No prior programming experience required
Basic computer literacy
Willingness to practice coding regularly

Coding Environment Options

Choose one of these Python environments to write and run your code:

VS Code (Recommended for professionals): Free Microsoft editor with Python extensions. Great for serious development work. Download: code.visualstudio.com

Google Colab: Browser-based notebooks with free cloud computing. Perfect for data analysis and learning. No installation needed. Access: colab.research.google.com

Cursor: AI-powered editor with intelligent code completion. Best for developers wanting AI assistance. Download: cursor.sh

Most data scientists start with Colab for learning, then move to VS Code for professional projects.

Learning Outcomes

By the end of this course, you will be able to: - Write Python programs to solve business problems - Work with different data types and structures - Read and process data from various sources - Apply Python skills to data analysis tasks