Computer Science 101: Master the Theory Behind Programming

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

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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