Phase 1: Python Basics & Environment Setup

• Introduction: History, features of Python, and compilation vs. interpretation.
• Environment Setup: Installing Python, configuring IDEs (VS Code, PyCharm, or Jupyter Notebook), and writing a "Hello World" program.
• Syntax Fundamentals: Indentation rules, comments, variables, and type casting.
• Input/Output Operations: Using print() formatting and capturing user inputs via input().

Phase 2: Operators & Control Flow

• Operators: Arithmetic, assignment, comparison, logical, identity, membership, and bitwise operators.
• Conditional Statements: if, elif, else, and nested conditions.
• Loops & Iteration: for loops, while loops, range sequences, and loop control statements (break, continue, pass).

Phase 3: Core Data Structures

• Strings: Slicing, indexing, immutability, and built-in string manipulation methods.
• Lists: Creating lists, indexing, slicing, mutability, nested lists, and list comprehensions.
• Tuples: Immutability syntax, packing, unpacking, and tuple operations.
• Dictionaries: Key-value pairs, accessing data, and dictionary methods.
• Sets: Unordered unique elements and set theory operations (union, intersection, difference).

Phase 4: Functional Programming & Modularization

• Functions: Defining functions, parameters, positional/keyword arguments, variable-length arguments (*args, **kwargs), and return values.
• Scope: Local vs. global variable scopes.
• Advanced Lambda Functions: Anonymous functions, map(), filter(), and reduce().
• Modules & Packages: Creating custom modules, importing standard libraries (e.g., math, datetime, os, random), and using pip.

Phase 5: Advanced Python Concepts

• File Handling: Reading, writing, appending files, and context managers (with statement).
• Exception Handling: Managing runtime errors using try, except, else, finally, and raising custom exceptions.
• Object-Oriented Programming (OOPs):
• Classes, objects, instance attributes, and methods.
• Constructors (__init__), class methods, and static methods.
• The Pillars: Inheritance (single, multiple, multilevel), polymorphism, encapsulation, and abstraction.
• Advanced Iterables: Generators, iterators, and custom decorators.

Phase 6: Core Tracks & Frameworks (Domain Specific)

• Data Science & ML Track: Learn NumPy for arrays, Pandas for data frames, and Matplotlib/Seaborn for data visualization.
• Web Development Track: Build backend web applications and REST APIs using frameworks like Django or Flask.
• Database Integration: Connecting Python to databases via SQL (MySQL/SQLite) or NoSQL (MongoDB).
• Web Scraping & Scripting: Automating browser tasks and parsing data via BeautifulSoup or Requests.