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Computational Thinking for Problem Solving

Курс от University of Pennsylvania

Начальный≈ 18.2 чАнглийский

О курсе

Computational thinking is the process of approaching a problem in a systematic manner and creating and expressing a solution such that it can be carried out by a computer. But you don't need to be a computer scientist to think like a computer scientist! In fact, we encourage students from any field of study to take this course. Many quantitative and data-centric problems can be solved using computational thinking and an understanding of computational thinking will give you a foundation for solving problems that have real-world, social impact. In this course, you will learn about the pillars of computational thinking, how computer scientists develop and analyze algorithms, and how solutions can be realized on a computer using the Python programming language. By the end of the course, you will be able to develop an algorithm and express it to the computer by writing a simple Python program. This course will introduce you to people from diverse professions who use computational thinking to solve problems. You will engage with a unique community of analytical thinkers and be encouraged to consider how you can make a positive social impact through computational thinking.

Навыки, которые вы освоите

Algorithms Python Programming Computational Thinking Computer Architecture Computer Programming Object Oriented Programming (OOP)Pseudocode Debugging Analytical Skills Problem Solving Computer Hardware Data Structures Analysis Computer Systems Program Development Programming Principles

Программа курса

4 модулей · 85 учебных материалов

01Pillars of Computational Thinking18 материалов

1.1 Introduction

Learning Style Preference SurveyЗадание 1.1 IntroductionВидео

1.2 Decomposition

1.2 DecompositionВидео 1.2 DecompositionЗадание

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Susan Davidson

Weiss Professor

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Обучение на Coursera

≈ 18.2 ч

4 модулей

Язык: Английский

Субтитры: Арабский, Французский, Бенгальский, Украинский, Китайский (Китай), Греческий, Итальянский, Бразильский португальский, Вьетнамский, Нидерландский, Корейский, Ория, Немецкий, Пушту, Урду, Русский, Тайский, Индонезийский, Шведский, Турецкий, Азербайджанский, Испанский, Дари, Хинди, Японский, Казахский, Венгерский, Польский

Computational Thinking for Problem Solving

О курсе

Навыки, которые вы освоите

Программа курса

1.1 Introduction

1.2 Decomposition

Учитесь у экспертов

Susan Davidson

1.3 Pattern Recognition

1.4 Data Representation and Abstraction

1.5 Algorithms

1.6 Case Studies

2.1 Finding the Largest Value

2.2 Linear Search

2.3 Algorithmic Complexity

2.4 Binary Search

2.5 Brute Force Algorithms

2.6 Greedy Algorithms

2.7 Case Studies

3.1 A History of the Computer

3.2 Intro to the von Neumann Architecture

3.3 Von Neumann Architecture Data

3.4 Von Neumann Architecture Control Structures

3.5 Expressing Algorithms in Pseudocode

3.6 Case Studies

4.1 Introduction to Python

4.2 Variables

4.3 Conditional Statements

4.4 Lists

4.5 Iteration

4.6 Functions

4.7 Classes and Objects

4.8 Case Studies

4.9 Course Conclusion