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Introduction to Computational Thinking

SynopsisIntroduction to Computational Thinking, available at $44.99,...
Introduction to Computational Thinking  No.1

Introduction to Computational Thinking, available at $44.99, has an average rating of 4.45, with 59 lectures, based on 117 reviews, and has 578 subscribers.

You will learn about Develop detailed step-by-step solutions to problems, think about and interpret data, and understand how different techniques improve problem solution efficiency This course is ideal for individuals who are Someone who wants to improve their attention to detail as they solve problems or Someone who wants to better understand how they can use and interpret data or Someone whos curious about how computation affects problem solutions in society It is particularly useful for Someone who wants to improve their attention to detail as they solve problems or Someone who wants to better understand how they can use and interpret data or Someone whos curious about how computation affects problem solutions in society.

Enroll now: Introduction to Computational Thinking

Summary

Title: Introduction to Computational Thinking

Price: $44.99

Average Rating: 4.45

Number of Lectures: 59

Number of Published Lectures: 59

Number of Curriculum Items: 59

Number of Published Curriculum Objects: 59

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

  • Develop detailed step-by-step solutions to problems, think about and interpret data, and understand how different techniques improve problem solution efficiency
  • Who Should Attend

  • Someone who wants to improve their attention to detail as they solve problems
  • Someone who wants to better understand how they can use and interpret data
  • Someone whos curious about how computation affects problem solutions in society
  • Target Audiences

  • Someone who wants to improve their attention to detail as they solve problems
  • Someone who wants to better understand how they can use and interpret data
  • Someone whos curious about how computation affects problem solutions in society
  • Computational thinking is critical for solving problems and using data effectively in modern society, but what is computational thinking anyway? Computational thinking is really a way to solve problems by specifying detailed, step-by-step solutions to those problems; collecting, representing, and analyzing data to support drawing conclusions or making decisions; and using a variety of techniques to improve the efficiency of our problem solutions.?

    This course is designed to help you learn key computational thinking topics and develop your skills in those areas.

    Learn About and Develop Computational Thinking Skills

  • Algorithms and Procedures
  • Data Collection, Representation, and Analysis
  • Problem Decomposition
  • Abstraction
  • Automation
  • Simulation
  • Parallelization
  • Contents and Overview

    In over 4 1/2 hours of content including 57 lectures, this course
    covers core computational thinking concepts. Four of the lectures
    include active learning activities integrated into the lectures, and
    the course also includes 13 additional exercises and topic
    understanding checks you can use to evaluate and hone your
    computational thinking skills.

    The course includes lots of practice because computational
    thinking is a? set of skills that most people need to develop by
    applying those skills rather than just hearing someone talk about
    them!

    When you finish the course, you should be able to develop detailed
    step-by-step solutions to a variety of problems, think about and
    interpret data, and understand how different techniques improve
    problem solution efficiency.

    Course Curriculum

    Chapter 1: Introduction

    Lecture 1: Course Introduction

    Lecture 2: Navigating a Udemy Course

    Lecture 3: Meet the Instructor

    Chapter 2: Fun With Algorithms

    Lecture 1: Section Introduction

    Lecture 2: Find the Queen

    Lecture 3: Nom Nom Nom

    Chapter 3: Data Collection

    Lecture 1: Section Introduction

    Lecture 2: Data Collection Problems

    Lecture 3: Deciding What Data to Collect

    Lecture 4: Finding the Data

    Lecture 5: Storing the Collected Data

    Lecture 6: Data Collection Activity

    Chapter 4: Algorithms and Procedures

    Lecture 1: Section Introduction

    Lecture 2: How Do I Get There?

    Lecture 3: The Caesar Cipher

    Chapter 5: Data Analysis

    Lecture 1: Section Introduction

    Lecture 2: Mean and Standard Deviation Part 1

    Lecture 3: Mean and Standard Deviation Part 2

    Lecture 4: Fictional Drug Trials

    Lecture 5: Continuous vs Discrete Data

    Lecture 6: Spelling Errors

    Chapter 6: Data Representation

    Lecture 1: Section Introduction

    Lecture 2: Histograms

    Lecture 3: Bar Charts

    Lecture 4: Line Graphs

    Lecture 5: Pie Charts

    Lecture 6: Scatterplots

    Lecture 7: Super Cool Representations

    Chapter 7: Problem Decomposition

    Lecture 1: Section Introduction

    Lecture 2: Going Green

    Lecture 3: Building a Chair

    Lecture 4: Designing a Car

    Chapter 8: Abstraction

    Lecture 1: Section Introduction

    Lecture 2: Rock and Roll

    Lecture 3: What Is a Chair?

    Lecture 4: Network Layers

    Chapter 9: Automation

    Lecture 1: Section Introduction

    Lecture 2: What is Automation?

    Lecture 3: Turning Up The Heat

    Lecture 4: Who You Gonna Call?

    Lecture 5: Whos Hungry?

    Lecture 6: CNC Machines

    Lecture 7: Robots

    Lecture 8: Driving

    Chapter 10: Simulation

    Lecture 1: Section Introduction

    Lecture 2: What is Simulation?

    Lecture 3: Simulating Computers with Computers

    Lecture 4: Training

    Lecture 5: Real-World Systems

    Lecture 6: Fitness

    Chapter 11: Parallelization

    Lecture 1: Section Introduction

    Lecture 2: What is Parallelization?

    Lecture 3: Sandwiches in Parallel

    Lecture 4: Doing Math in Parallel

    Lecture 5: Building a Video Game in Parallel

    Lecture 6: Pipelines

    Lecture 7: Parallel Processing

    Lecture 8: Parallelization Activity

    Chapter 12: Course Wrapup

    Lecture 1: Course Wrapup

    Instructors

  • Introduction to Computational Thinking  No.2
    Tim Dr. T Chamillard
    Teacher, Author, and Indie Game Developer
  • Rating Distribution

  • 1 stars: 2 votes
  • 2 stars: 7 votes
  • 3 stars: 15 votes
  • 4 stars: 34 votes
  • 5 stars: 59 votes
  • Frequently Asked Questions

    How long do I have access to the course materials?

    You can view and review the lecture materials indefinitely, like an on-demand channel.

    Can I take my courses with me wherever I go?

    Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!