introduction-to-computational-thinking-and-data-science

Introduction to Computational Thinking and Data Science

Computational Thinking (CT) is a problem solving process that includes a number of characteristics and dispositions. CT is essential to the development of computer applications, but it can also be used to support problem solving across all disciplines, including math, science, and the humanities.

Lesson: 10
08:03:11 Hrs
Last Updated 07-03-2024

Curriculum for this course Lesson: 10 08:03:11 Hrs

Section 1: Introduction, Optimization Problems Lesson

Lesson 1: Introduction, Optimization Problems00:40:56

Section 2: Optimization Problems Lesson

Lesson 2: Optimization Problems00:48:03

Section 3: Graph-theoretic Models Lesson

Lesson 3: Graph-theoretic Models00:50:10

Section 4: Stochastic Thinking Lesson

Lesson 4: Stochastic Thinking00:49:49

Section 5: Random Walks Lesson

Lesson 5: Random Walks00:49:20

Section 6: Monte Carlo Simulation Lesson

Lesson 6: Monte Carlo Simulation00:50:04

Section 7: Confidence Intervals Lesson

Lesson 7: Confidence Intervals00:50:28

Section 8: Sampling and Standard Error Lesson

Lesson 8: Sampling and Standard Error00:46:44

Section 9: Understanding Experimental Data Lesson

Lesson 9: Understanding Experimental Data00:47:05

Section 10: Understanding Experimental Data (cont.) Lesson

Lesson 10: Understanding Experimental Data (cont.)00:50:32

Description

Computational Thinking (CT) is a problem solving process that includes a number of characteristics and dispositions. CT is essential to the development of computer applications, but it can also be used to support problem solving across all disciplines, including math, science, and the humanities..

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