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Understanding the computational thinking needed in the AI era

Computational thinking isn't something that only computer science majors learn. Every profession has problems that need to be solved, and computational thinking can be used to solve those problems.

(4.3) 4 reviews

17 learners

Level Beginner

Course period 12 months

  • sdj0831
Computer Architecture
Computer Architecture
Parallel Processing
Parallel Processing
Business Problem Solving
Business Problem Solving
data-transformation
data-transformation
Computer Architecture
Computer Architecture
Parallel Processing
Parallel Processing
Business Problem Solving
Business Problem Solving
data-transformation
data-transformation

Reviews from Early Learners

Reviews from Early Learners

4.3

5.0

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100% enrolled

I liked that it was easy to understand the overall content.

What you will gain after the course

  • Computational thinking

  • Algorithm

  • Multimedia processing

  • Parallel computing

  • Artificial Intelligence Basics

  • Information protection techniques

As the AI era fully takes hold in our lives, the importance of computational thinking is growing. Computational thinking refers to a computer-like approach to problem-solving. In other words, it involves decomposing complex problems, recognizing patterns, simplifying problems through abstraction, and designing algorithms. These skills are essential for creative problem-solving and innovation in current and future societies.

So now let's learn how to develop computational thinking.

1. Decomposition : Breaking down a large problem into smaller ones. For example, when developing a complex program, breaking it down into smaller units makes it easier to manage.

2. Pattern Recognition : To solve a problem, you need to find patterns or similarities. Finding and applying similar patterns from problems you've already solved can help you solve problems much faster.

3. Abstraction : Complex problems need to be expressed in simpler terms. This is a way to understand the core of the problem by focusing on important information and eliminating unnecessary information.

4. Algorithmic Thinking : You need to think about a step-by-step procedure for problem solving. This involves creating clear instructions and designing specific steps to solve the problem.

5. Evaluation and Iteration : Evaluate your solution, refine it when necessary, and iterate. It's difficult to create a perfect solution from scratch, so the process of trying, evaluating, and refining is crucial.

In summary, computational thinking consists of five core elements: problem decomposition, pattern recognition, abstraction, algorithmic thinking, and evaluation and iteration. These five elements can dramatically improve our problem-solving abilities.

Recommended for
these people

Who is this course right for?

  • All members of society who face various problems and challenges

  • Project managers who must clearly communicate technical requirements

  • Anyone who wants to develop the ability to think and analyze smartly

  • Anyone curious about computational thinking in the AI era

Need to know before starting?

  • No pre-training required

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4.3

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To help you upgrade your capabilities, DefecUp creates easy and practical convergence-style e-learning content. There are two brands operated by DefecUp.

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"Turning learning into growth"

"Turning learning into growth"

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23 lectures ∙ (4hr 54min)

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4.3

4 reviews

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