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Computational Thinking for Problem Solving

A comprehensive beginner-friendly course that provides practical insights into computational thinking and problem-solving, perfect for those seeking to develop analytical skills.

access

Lifetime

level

Beginner

certificate

Certificate of completion

language

English

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What you will learn in Computational Thinking for Problem Solving

  • Grasp the four pillars of computational thinking: decomposition, pattern recognition, data representation and abstraction, and algorithms.

  • Develop and analyze algorithms, understanding their efficiency and application.

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  • Comprehend the fundamental operations of modern computers, including the von Neumann architecture.

  • Translate problem-solving strategies into Python code, even without prior programming experience.

Program Overview

Module 1: Pillars of Computational Thinking
⏳  3 hours

  • Introduction to the core concepts of computational thinking and their application in problem-solving.

Module 2: Expressing and Analyzing Algorithms
⏳  4 hours

  • Learn to develop algorithms and assess their performance, including understanding algorithmic complexity.

Module 3: Fundamental Operations of a Modern Computer
⏳  3 hours

  • Explore how computers execute instructions and manage data, including an overview of the von Neumann architecture. 

Module 4: Applied Computational Thinking Using Python
⏳  6 hours

  • Apply computational thinking by writing simple Python programs to solve problems.

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Job Outlook

  • Completing this course enhances problem-solving and analytical skills applicable across various industries.

  • Provides a foundation for further studies in computer science and programming.

  • Equips learners with skills relevant to roles requiring analytical and computational thinking.

9.7Expert Score
Highly Recommended
The "Computational Thinking for Problem Solving" course offers a comprehensive introduction to computational thinking principles. It's ideal for beginners aiming to develop problem-solving skills applicable in various domains.
Value
9
Price
9.2
Skills
9.6
Information
9.7
PROS
  • No prior experience required, making it accessible to beginners.
  • Self-paced learning with a flexible schedule
  • Taught by experienced instructors from the University of Pennsylvania.
  • Provides a holistic view of computational thinking, encompassing theoretical and practical perspectives.
CONS
  • Requires consistent time commitment to complete all modules within the recommended timeframe.
  • May require supplementary resources for those seeking in-depth technical skills beyond the scope of the course.

Specification: Computational Thinking for Problem Solving

access

Lifetime

level

Beginner

certificate

Certificate of completion

language

English

Computational Thinking for Problem Solving
Computational Thinking for Problem Solving
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