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Foundations of Computer Science: Theory and Practice

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Foundations of Computer Science: Theory as well as Practice

Learn the key subject matters of Computer Science as well as perform all of them for total proficiency – Free Course

Description

In this training course, you will definitely find out:-

  • Develop the capability to produce extra reliable as well as successful programs.
  • Gain a much deeper understanding of information technology principles.
  • Learn the abilities you’ll require to prosper in coding job interviews.
  • You can easily accelerate your treatment for SE Factory’s offline training courses through completing the document listed below.

Syllabus:-

  • Welcome to the Foundations of Computer Science!
  • Python, why our company’re utilizing it in this particular training course
  • Scalar items, the easy kinds
  • The kinds of items in Python
  • On kinds
  • Arithmetic drivers
  • Arithmetic Operators
  • Variables, utilizing titles rather than merely market values
  • Operator priority
  • Calculate the amount of pair of amounts
  • Handling input as well as outcome
  • Comparisons
  • Introducing Strings
  • Logic Operators
  • Control Flow – If claim
  • Selection
  • 2.1- Square Root
  • Control Flow – Loops (while, for)
  • Control Flow – Break
  • Control Flow – While vs For
  • Repetition
  • 2.2 – Odd components
  • 2.3 – Square of an Integer
  • 2.5 – Cubic Root
  • 2.4 – Perfect Number
  • Strings cutting as well as inscribing
  • Variable extent as well as functionalities
  • Strings extensive
  • Introducing functionalities
  • Functions as well as recursion
  • Find amount recursively
  • Count numbers recursively
  • Reverse a variety
  • 2.1 – Palindrome Strings
  • 2.4 – Coprimes
  • Data frameworks overview
  • Lists (component 1)
  • Tuples
  • Lists (component 2) – Aliases as well as Sorting
  • Dictionaries
  • 3.4 – Boiling Point
  • 3.2 – List Jumps
  • 3.1 – Sieve of Eratosthenes
  • 3.5 – Cycles
  • Exponential as well as Logarithmic Function Review
  • Algorithmic Complexity Rationale
  • Big O Notation (Part 1)
  • Big O Notation (Part 2) – Quadratic Complexity Example
  • 4.2 – Permuted Strings
  • 4.4 – Euclidean Distance
  • 2.3 – Wolves as well as Deer
  • 1.4 – Spiral Index
  • Bisection Search
  • Sorting Algorithms Intro
  • Bubble Sort
  • Selection Sort
  • 5.2 – Permutation Cycle Length
  • 5.4 – Matrix Search
  • 5.3 – Fair Partition
  • Introduction to Classes
  • Linked List
  • Stack
  • Queue
  • Priority Queue
  • 6.1 – List Mode
  • 6.2 – Filtering Linked List
  • 6.3 – Well Formed String
  • 6.4 – Linked List Equality
  • 6.5 – Lowest-K Elements
  • 6.6 – Merging Linked Lists
  • Hash Table
  • Trees
  • Binary Search Tree (BST)
  • 7.1 – BST Descending Order Traversal
  • 7.2 – BST Element Filtering
  • 7.3 – Reverse BST in Place
  • 7.4 – BST Levels
  • 7.5 – Balanced BST
  • Graphs
  • Depth First Search (DFS)
  • Breadth First Search (BFS)
  • 8.4 – Depth in Graph
  • 8.1 – Maze
  • 8.3 – Clique
  • 8.2 – Graph Cycle

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