Detailed Course Syllabus

• Welcome to the course & expectations
• What is Python? Why learn it?
• Installation verification (Python & VS Code)
• Your first Python program: print() function
• Understanding comments and basic syntax
• Practice: Print statements and simple output

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• What are variables? How to create them
• Data types: int, float, string, bool
• Type conversion (int to string, etc.)
• Input from user using input() function
• Practice: Create variables, take user input, print values

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• Arithmetic operators: +, -, *, /, //, %, **
• Assignment operators: =, +=, -=, etc.
• Comparison operators: ==, !=, <, >, <=, >=
• Order of operations (BODMAS)
• Practice: Calculator programs, math operations

• if, elif, else statements
• Logical operators: and, or, not
• Nested if conditions
• Writing clean conditional logic
• Project: Simple login program, age checker

• for loops: range(), enumerate()
• while loops: conditions and infinite loops
• break and continue statements
• Nested loops
• Practice: Print patterns, multiplication tables

• Complex loop patterns
• Finding prime numbers
• Fibonacci sequence
• Project: Number guessing game
• Debugging loop errors

• Creating lists and indexing
• List methods: append(), remove(), pop(), insert()
• List slicing and iteration
• List comprehension basics
• Practice: Manipulating lists, searching elements

• String manipulation: slicing, indexing
• String methods: upper(), lower(), split(), join()
• String formatting: f-strings, .format()
• Finding substrings, replacing text
• Project: Simple text analyzer

• Defining and calling functions
• Parameters and return values
• Default arguments
• Scope: local vs global variables
• Practice: Rewrite calculator using functions

• *args and **kwargs
• Lambda functions
• Decorators basics
• Recursive functions
• Project: Modular calculator with multiple functions

• Creating and accessing dictionaries
• Dictionary methods: keys(), values(), items()
• Nested dictionaries and lists
• Dictionary comprehension
• Project: Contact manager application

• Tuples: immutable sequences, packing/unpacking
• When to use tuples vs lists
• Sets: unique elements, set operations
• Union, intersection, difference
• Practice: Data deduplication using sets

• Reading files: open(), read(), readline(), readlines()
• Writing and appending to files
• Working with CSV files
• Using with statement (context manager)
• Project: File-based data storage system

• try, except, else, finally blocks
• Common exceptions: ValueError, TypeError, FileNotFoundError
• Custom exceptions
• Raising exceptions manually
• Practice: Robust file reading with error handling

• What are REST APIs? HTTP methods (GET, POST)
• JSON format: parsing and creating
• Using the requests library
• API keys and authentication basics
• Practice: Fetch data from a public API

• OpenWeatherMap API integration
• Parsing nested JSON responses
• Displaying data cleanly in terminal
• Saving results to a file
• Project: Complete real-time weather application

• What are LLMs? How ChatGPT and Claude work
• OpenAI API setup and authentication
• Making your first API call to GPT
• Prompt engineering basics
• Practice: Build a simple Q&A script using OpenAI API

• Conversation history and context management
• Claude API integration
• Rate limiting and error handling for APIs
• Saving chat history to files
• Project: Complete terminal-based AI chatbot

• NumPy arrays vs Python lists
• Array creation, indexing, slicing
• Vectorized operations and broadcasting
• Mathematical functions with NumPy
• Practice: Statistical analysis on datasets

• DataFrames and Series
• Reading CSV and JSON files with Pandas
• Data cleaning: handling missing values, duplicates
• Filtering, grouping, and aggregating data
• Project: Analyze a real-world dataset

• How websites work: HTML structure, DOM
• BeautifulSoup: parsing HTML
• Finding elements by tag, class, ID
• Scraping tables and lists
• Project: Scrape product prices or news headlines

• Automating file and folder operations
• Sending emails with smtplib
• Scheduling tasks with Python
• Working with regular expressions (regex)
• Project: Automated email sender or file organizer

• Choose your capstone: AI Analyzer, Automation Suite, or Web Scraper
• Combine Python fundamentals + APIs + data + AI
• Code review and best practices
• Performance optimization tips
• Writing clean, readable, documented code

• GitHub: push your project, write a README
• Deploying Python apps (basic hosting)
• Interview preparation: common Python questions
• Building your developer portfolio
• Course wrap-up and next steps