Programming in Python Course Syllabus
Full curriculum breakdown — modules, lessons, estimated time, and outcomes.
Overview: This hands-on Python course is designed for beginners to build a strong foundation in programming using Python. Through interactive coding exercises and practical projects, learners will progress from basic syntax to object-oriented programming and file handling. The course spans approximately 20 hours of content, structured into eight modules that balance theory with real-world coding practice, making it ideal for aspiring developers aiming to enter the tech industry.
Module 1: Introduction to Python
Estimated time: 1.5 hours
- What is Python
- Python syntax and indentation
- Variables and assignment
Module 2: Working with Data Types
Estimated time: 2 hours
- Strings and string operations
- Numbers and arithmetic
- Booleans and logical values
- Type conversion
Module 3: Conditionals and Loops
Estimated time: 2.5 hours
- If-else statements
- While loops
- For loops
- Nested control flows
Module 4: Functions and Scope
Estimated time: 3 hours
- Defining and calling functions
- Function parameters and return values
- Local and global scope
Module 5: Data Structures in Python
Estimated time: 3 hours
- Lists and list operations
- Tuples
- Sets
- Dictionaries
Module 6: Object-Oriented Programming
Estimated time: 3.5 hours
- Classes and objects
- Methods and constructors
- Inheritance
Module 7: File I/O and Error Handling
Estimated time: 2 hours
- Reading from and writing to files
- Exception handling with try-except
Module 8: Capstone Practice Projects
Estimated time: 2.5 hours
- Solve real-world problems using control flow
- Implement data structures and functions in projects
- Apply object-oriented programming concepts
Prerequisites
- No prior programming experience required
- Basic computer literacy
- Access to a web browser
What You'll Be Able to Do After
- Master foundational programming concepts through Python
- Work with data structures including lists, dictionaries, and sets
- Use conditionals, loops, and functions to build logic-driven applications
- Apply object-oriented programming with classes, methods, and inheritance
- Write modular, reusable, and maintainable Python code