Computational Thinking for Problem Solving Course Syllabus

Overview: This beginner-friendly course introduces the foundational concepts of computational thinking and equips learners with problem-solving strategies applicable across disciplines. The course is structured into four core modules followed by a final project, totaling approximately 16 hours of self-paced learning. Each module builds essential skills step-by-step, from understanding computational principles to applying them in Python programming. Designed for accessibility, no prior experience is required, making it ideal for beginners aiming to develop analytical and computational reasoning abilities.

Module 1: Pillars of Computational Thinking

Estimated time: 3 hours

• Introduction to computational thinking
• Decomposition of complex problems
• Pattern recognition in problem-solving
• Data representation and abstraction
• Formulating algorithms as step-by-step solutions

Module 2: Expressing and Analyzing Algorithms

Estimated time: 4 hours

• Developing clear and precise algorithms
• Representing algorithms using pseudocode and flowcharts
• Understanding algorithmic efficiency
• Analyzing time complexity and performance

Module 3: Fundamental Operations of a Modern Computer

Estimated time: 3 hours

• Overview of computer architecture
• The von Neumann model and its components
• How computers execute instructions
• Data storage and processing fundamentals

Module 4: Applied Computational Thinking Using Python

Estimated time: 6 hours

• Introduction to Python programming for beginners
• Translating algorithms into Python code
• Implementing problem-solving strategies using computational thinking

Module 5: Final Project

Estimated time: 4 hours

• Define a real-world problem suitable for computational analysis
• Apply decomposition, pattern recognition, and abstraction to model the solution
• Develop and implement an algorithm in Python to solve the problem

Prerequisites

• No prior programming experience required
• Basic computer literacy
• Willingness to think logically and systematically

What You'll Be Able to Do After

• Apply the four pillars of computational thinking to real-world problems
• Design and analyze algorithms for efficiency and correctness
• Understand how modern computers process and store data
• Translate problem-solving strategies into working Python programs
• Solve practical problems using structured computational approaches