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Computer Science 101- Master the Theory Behind Programming

  • Development
  • Mar 20, 2025
SynopsisComputer Science 101: Master the Theory Behind Programming, a...
Computer Science 101- Master the Theory Behind Programming  No.1

Computer Science 101: Master the Theory Behind Programming, available at $94.99, has an average rating of 4.6, with 103 lectures, 9 quizzes, based on 5962 reviews, and has 35209 subscribers.

You will learn about Understand the Fundamental Theories of Algorithm Analysis Be able to Compare Various Algorithms Understand When to use Different Data Structures and Algorithms Understand the Fundamentals of Computer Science theory Understand the Core Sorting Algorithms This course is ideal for individuals who are Anyone who wants to become a Good Programmer or Anyone interested in the Computer Science Discipline or Anyone who wants to learn how to problem solve like a Computer Scientist It is particularly useful for Anyone who wants to become a Good Programmer or Anyone interested in the Computer Science Discipline or Anyone who wants to learn how to problem solve like a Computer Scientist.

Enroll now: Computer Science 101: Master the Theory Behind Programming

Summary

Title: Computer Science 101: Master the Theory Behind Programming

Price: $94.99

Average Rating: 4.6

Number of Lectures: 103

Number of Quizzes: 9

Number of Published Lectures: 103

Number of Published Quizzes: 9

Number of Curriculum Items: 112

Number of Published Curriculum Objects: 112

Original Price: $39.99

Quality Status: approved

Status: Live

What You Will Learn

  • Understand the Fundamental Theories of Algorithm Analysis
  • Be able to Compare Various Algorithms
  • Understand When to use Different Data Structures and Algorithms
  • Understand the Fundamentals of Computer Science theory
  • Understand the Core Sorting Algorithms
  • Who Should Attend

  • Anyone who wants to become a Good Programmer
  • Anyone interested in the Computer Science Discipline
  • Anyone who wants to learn how to problem solve like a Computer Scientist
  • Target Audiences

  • Anyone who wants to become a Good Programmer
  • Anyone interested in the Computer Science Discipline
  • Anyone who wants to learn how to problem solve like a Computer Scientist
  • Master the Theory to Becoming a Good Programmer!?

    If you’re looking to learn the theory that makes great programmers,?you’ve come to the right place!?This course is perfect for anyone interested in learning the fundamentals to Computer Science Theory.?

    No Previous Experience Necessary!?

    Computer science and technology are often thought of as things only for “analytical minds”. I believe however that technology and it’s theory are for everyone. So I designed this?course to?teach each topic in a variety of?easy to digest ways. Through these multiple reinforcing steps, I believe anyone can follow along and succeed!?

    Why is the Theory of Programming Important??

    Understanding?Computer Science theory is what sets apart?Great programmers?from average ones. Programming theory is something that transcends a single programming language. It gives you skills and techniques you can apply to any programming language you touch. Learning the theory behind programming is just as important, if not more important than learning a singular programming language like Java or C++.

    Programming is all about problem solving. Analyzing a problem, and being able to figure out a way that a computer can help with that problem. Computer Science is the practice of this analysis process. It goes over the techniques and knowledge necessary to design efficient and sustainable code.?

    So if you want to begin setting yourself apart from the average programmers, this is the course for you!?

    Enroll Now and you’ll Learn:?

  • Binary Number System

  • N Notation

  • Big O Notation

  • How to Analyze a Program

  • Arrays and?their Advantages

  • Nodes and their Importance

  • Linked?Lists and their Advantages and Implementations

  • Stacks implemented with Arrays and Linked?Lists

  • Queues Implemented with Arrays and Linked Lists

  • Various Sorting Algorithms and Their Comparisions

  • Trees and Binary Search Trees

  • And Much Much More!?

  • My?Guarantee

    I am so confident you will enjoy this course, I offer a 100%?30-day money-back guarantee through Udemy.?If you are not happy with your purchase, I have no problem with giving your money back!?

    Are You Ready to Get Started??

    I will be waiting for you inside the course!?

    Remember, this is an online course, so you can take it at your own pace.?Are you busy right now??That’s okay. Enroll today, and take the course at your own pace.

    Thanks so much for your interest in this Computer Science 101 Course!?

    See you inside!

    Kurt

    Course Curriculum

    Chapter 1: Introduction

    Lecture 1: Introduction

    Lecture 2: Binary Number Introduction

    Lecture 3: Binary Deca Number Conversion

    Lecture 4: Binary Number System Notes

    Chapter 2: Analyzing Algorithms

    Lecture 1: All Notes

    Lecture 2: Introduction to Time-Complexity

    Lecture 3: Math Refresher: Logarithmic Functions

    Lecture 4: Math Refresher: Factorial Functions

    Lecture 5: Math Refresher: Algebraic Expressions

    Lecture 6: Math Refresher Notes

    Lecture 7: n-notation Introduction

    Lecture 8: n-notation Scaling

    Lecture 9: n-notation Example

    Lecture 10: Big O Notation

    Lecture 11: n-Notation Notes

    Lecture 12: Big O Real-World Example

    Chapter 3: Arrays

    Lecture 1: How is Data Stored?

    Lecture 2: Fixed Array Introduction

    Lecture 3: Fixed Array Run Times

    Lecture 4: Binary Search Algorithm (Fixed Array Sorted Search)

    Lecture 5: Fixed Array Notes

    Lecture 6: Circular Array Intro + Modulo

    Lecture 7: Circular Array Deep Dive

    Lecture 8: Circular Array Code Example

    Lecture 9: Dynamic Arrays

    Lecture 10: O(1) Approximation

    Lecture 11: Circular and Dynamic Array Notes

    Lecture 12: Array Review

    Lecture 13: Array Real World + Code Examples

    Chapter 4: Linked Lists

    Lecture 1: Nodes

    Lecture 2: Singly Linked List

    Lecture 3: Linked List Run Times

    Lecture 4: Singly Linked-List Code Example

    Lecture 5: Singly-Linked List Notes

    Lecture 6: Doubly Linked Lists

    Lecture 7: Tail Pointers

    Lecture 8: Doubly-Linked List and Tail Pointer Notes

    Lecture 9: Linked List Real World Examples

    Lecture 10: Linked List Review

    Chapter 5: Stacks and Queues

    Lecture 1: Stacks

    Lecture 2: Stack Examples

    Lecture 3: Stack Code Example

    Lecture 4: Stack Notes

    Lecture 5: Queues

    Lecture 6: Queue Examples

    Lecture 7: Queue Code Example

    Lecture 8: Queue Notes

    Lecture 9: Queue and Stack Run Times

    Lecture 10: Stack and Queue Real World Examples

    Lecture 11: Stacks and Queues Quiz Explanation

    Chapter 6: Sorting Algorithms

    Lecture 1: Introduction to Sorting Algorithms

    Lecture 2: Bubble Sort

    Lecture 3: Bubble Sort Coding Example

    Lecture 4: Bubble Sort Notes

    Lecture 5: Selection Sort

    Lecture 6: Selection Sort Code Example

    Lecture 7: Selection Sort Notes

    Lecture 8: Insertion Sort

    Lecture 9: Insertion Sort Notes

    Lecture 10: Recursion

    Lecture 11: Quick Sort

    Lecture 12: Quick Sort Run Time

    Lecture 13: Quick Sort Notes

    Lecture 14: Quick Sort Code Example

    Lecture 15: Merge Sort

    Lecture 16: Merge Sort Run Times

    Lecture 17: Merge Sort Notes

    Lecture 18: Merge Sort Code Example

    Lecture 19: Stable vs NonStable

    Lecture 20: Stable Vs NonStable Notes

    Lecture 21: Sorting Algorithm Real World Examples

    Chapter 7: Trees

    Lecture 1: Trees

    Lecture 2: Binary Search Trees

    Lecture 3: Binary Search Tree Run Times

    Lecture 4: Tree Code Example

    Lecture 5: Tree Notes

    Lecture 6: Tree Traversals

    Lecture 7: Tree Real World Examples

    Chapter 8: Heaps

    Lecture 1: Heaps Introduction

    Lecture 2: Heap Analysis

    Lecture 3: Heaps Real World Examples

    Lecture 4: Heap Notes

    Chapter 9: Graphs

    Instructors

  • Computer Science 101- Master the Theory Behind Programming  No.2
    Kurt Anderson
    Multi-Media Designer, Computer Scientist, YouTube Guru
  • Rating Distribution

  • 1 stars: 42 votes
  • 2 stars: 91 votes
  • 3 stars: 476 votes
  • 4 stars: 1974 votes
  • 5 stars: 3379 votes
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