MITx: Introduction to Computer Science and Programming Using Python course Syllabus
Full curriculum breakdown — modules, lessons, estimated time, and outcomes.
Overview (80-120 words) describing structure and time commitment.
Module 1: Foundations of Computer Science
Estimated time: 12 hours
- How computers process information
- Abstraction in computing
- Algorithmic thinking
- Solving structured programming problems
Module 2: Python Programming Fundamentals
Estimated time: 16 hours
- Variables, data types, and expressions
- Control flow: conditionals and loops
- Functions and code modularity
- Lists, dictionaries, and common data structures
Module 3: Algorithms and Problem Solving
Estimated time: 14 hours
- Designing search algorithms
- Sorting algorithm implementation
- Conceptual analysis of time complexity
- Applying logical reasoning to computational problems
Module 4: Object-Oriented Programming
Estimated time: 10 hours
- Creating classes and objects in Python
- Encapsulation and data abstraction
- Structuring larger programs using OOP principles
Module 5: Computational Complexity and Efficiency
Estimated time: 8 hours
- Basics of computational complexity
- Measuring algorithm efficiency
- Practical trade-offs in program design
Module 6: Final Project
Estimated time: 20 hours
- Design a Python program solving a real-world problem
- Apply core programming and algorithmic concepts
- Submit code with documentation and efficiency analysis
Prerequisites
- Basic high school mathematics
- Familiarity with algebraic concepts
- Some comfort with logical reasoning
What You'll Be Able to Do After
- Understand foundational computer science concepts
- Write Python programs to solve real-world problems
- Apply problem-solving and algorithmic thinking
- Work with functions, control flow, and data structures
- Analyze basic computational efficiency