🐍 Complete Python Syllabus – Beginner to Advanced

🔹 MODULE 1: PYTHON FOUNDATIONS

Objective: Build a strong foundation in core syntax and logic.

• What is Python & where is it used?

• Installing Python, Jupyter Notebook, VS Code

• Running your first Python script

• Variables, data types, and type casting

• Comments and code documentation

• Print statements and string formatting

🔹 MODULE 2: CONTROL FLOW & LOGIC

Objective: Make your code think and decide.

• If, elif, else conditions

• Comparison and logical operators

• Loops: for, while

• break, continue, pass

• Real-world condition-based use cases

🔹 MODULE 3: DATA STRUCTURES

Objective: Store, access, and manipulate data like a pro.

• Lists, Tuples, Sets, Dictionaries

• Indexing and slicing

• List comprehensions

• Dictionary operations and looping

• Nesting data structures

🔹 MODULE 4: FUNCTIONS & MODULAR CODING

Objective: Write clean, reusable code.

• Defining functions with def

• Parameters and return values

• Lambda functions

• *args, **kwargs

• Scope: local vs. global

• Modular programming and importing scripts

🔹 MODULE 5: FILE HANDLING & EXCEPTIONS

Objective: Read, write, and manage files with Python.

• Working with text, CSV, and JSON files

• Reading and writing Excel files using openpyxl or pandas

• File system operations (os, shutil)

• Try/except blocks for error handling

• Creating robust scripts with exception logic

🔹 MODULE 6: PYTHON FOR AUTOMATION

Objective: Automate your daily tasks and boost productivity.

• Automating Excel reports with pandas, openpyxl

• Automating emails with smtplib

• Web scraping using requests, BeautifulSoup

• Scheduling and auto-running scripts

• Working with APIs (REST basics)

🔹 MODULE 7: PYTHON FOR DATA ANALYSIS

Objective: Analyze and visualize data effortlessly.

• Introduction to NumPy and Pandas

• Data cleaning and manipulation

• Filtering, sorting, grouping, pivoting

• Visualizing data with Matplotlib and Seaborn

• Exporting reports to Excel/CSV/PDF

🔹 MODULE 8: OBJECT-ORIENTED PROGRAMMING (OOP)

Objective: Build scalable and structured applications.

• Classes and Objects

• Constructors (__init__)

• Inheritance and Polymorphism

• Encapsulation and Abstraction

• Use cases: task manager, employee system

🔹 MODULE 9: INTRO TO MACHINE LEARNING (Optional Add-on)

Objective: Build your first ML model with no math anxiety.

• Introduction to scikit-learn

• Loading datasets, train-test split

• Classification and regression basics

• Model evaluation: accuracy, confusion matrix

• Real-world ML use case: prediction model

🔹 MODULE 10: FINAL PROJECTS & CAPSTONE

Objective: Apply everything in a practical, hands-on project.

• Project 1: Automate a sales dashboard report in Excel

• Project 2: Build a data scraper + auto emailer

• Project 3: Create a mini data analytics tool using Pandas

• Project 4: Optional: Basic ML model for churn prediction

🔹 BONUS: BEST PRACTICES & TOOLING

• Git & GitHub for version control

• Writing clean, readable code (PEP8)

• Working with virtual environments

• Python Package Index (PyPI) & pip

• Creating and using custom modules