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Master the Theory Behind Programming

(43 Ratings) 3983 Students Enrolled
Created By Kavin kumar Last Updated Mon, 16-Mar-2020 English
  • Course Duration
    6 Hours
  • Mode of Training
    Self-Paced
  • Lessons
    44 Lessons
  • Placement Assistance
    Guaranteed
$ 99.99 $ 8.99 91% off 100% Money Back Guarantee
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What Will I Learn?
  • Understandings of the Fundamental Theories of Algorithm Analysis
  • When and where to use the different Data Structures & Algorithms
  • Learn how to understand the various Sorting Algorithms
  • Understand the various Data Structures and their Applications
  • Understand the Fundamentals of Computer Science Theory

Requirements
  • Basic Computer Science Knowledge
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Description

This course is for one who wants to learn Programming without any prior knowledge. If you want to learn the theory, that makes great programmers, you've come to right place! 

Computer Science and Technology are often thought of as things only for 'analytical minds'. This course is designed to teach each topic in a variety of ways. Programming theory is something that transcends a single programming language. This gives you skills and techniques that you can apply to any programming language.

Programming is all about problem solving. Analyzing a problem and being figure up the way to solve the problem is very important. We need to build the techniques and knowledge necessary to design efficient and sustainable code.

The following concepts are learned in this course:

  • Binary Number system
  • N Notation
  • Big O Notation
  • How to Analyze a Program
  • Arrays and their Advantages
  • Nodes and their importance
  • Linked List and their Applications
  • Stack Data Structure implemented using Linked Lists and Arrays
  • Various Sorting Algorithms and their Comparisons
  •  Trees and Binary Search Trees
Curriculum For This Course
44 Lessons 6 Hours
  • Introduction to Time-Complexity 00:02:12 Preview
  • Math Refresher: Logarithmic Functions 00:11:08
  • Math Refresher: Factorial Functions 00:03:19
  • Math Refresher: Algebraic Expressions 00:02:48
  • n-notation 00:18:56 Preview
  • Big O Notation 00:12:59
  • Big O Real-World Example 00:09:52
  • How is Data Stored? 00:08:38 Preview
  • Fixed Array Introduction 00:05:09
  • Fixed Array Run Times 00:12:23
  • Binary Search Algorithm (Fixed Array Sorted Search) 00:10:00
  • Circular Arrays 00:08:01
  • Dynamic Arrays 00:15:52
  • Array Review 00:07:57
  • Array Real World Examples 00:05:42
  • Nodes 00:04:20
  • Linked List 00:13:36 Preview
  • Linked List Run Times 00:14:59
  • Doubly Linked Lists 00:08:07
  • Tail Pointers 00:05:14
  • Linked List Review 00:03:31
  • Linked List Real World Examples 00:03:00
  • Stacks 00:09:41
  • Stack Examples 00:11:05
  • Queues 00:08:48
  • Queue Examples 00:09:42
  • Queue and Stack Run Times 00:06:04
  • Stack and Queue Real World Examples 00:07:01
  • Introduction to Sorting Algorithms 00:01:41 Preview
  • Bubble Sort 00:10:13
  • Selection Sort 00:09:50
  • Insertion Sort 00:09:04
  • Quick Sort 00:14:38
  • Quick Sort Run Time 00:10:31
  • Merge Sort 00:11:58
  • Merge Sort Run Times 00:07:39
  • Stable vs NonStable 00:06:34
  • Sorting Algorithm Real World Examples 00:04:02
  • Basics of Trees 00:07:37 Preview
  • Binary Search Trees 00:08:35
  • Binary Search Tree Run Times 00:07:37
  • Tree Traversals 00:13:04
  • Tree Real World Examples 00:04:30
  • Timing Project Preparation 00:06:48

Master the Theory Behind Programming