Competitive Programming with C++ & Python

About The Program:

With the belief to build a healthy ecosystem as per the Industry Standards REGex Software brings Training Program on “Competitive Programming with C++ & Python”. We organize Training Program for improving the knowledge and skills of the Students/Professionals, so that they can become expert in the field of Competitive Programming and get their Dream Job in Software Development Field in Big MNCs.

REGex Software Services’s Competitive Programming course is a valuable resource for beginners and experts. This program will introduce you to C++, Data Structures, Python and Interview Based Questions of Product Based Companies from Basics to Advance. If you are preparing for a coding interview, REGex introduce this course for you.

What People Tell About Us

What you will Learn

  • C++ & Python (Basics to Advance)
  • Data Structures & Algorithms
  • Problem Solving Approach
  • How to Crack Interview Questions in Product Based Companies
  • Learn how to use Data Structures & Algorithms in Problem Solving

Study Material

  • E-Notes
  • Assignments per day
  • Poll test per day
  • Weekly Tests
  • 80+ hours on demand Live Video Lectures
  • Offline Access of Lecture Videos & Notes
  • 24*7 Mentorship Support

  •  Working on Live Projects

Output

  • Good Programmer.
  • Able to think out of the box.
  • Expertise in different Domain like C++, Python, Data Structures & Algorithms, Problem Solving
  • Able to solve many Interview Questions of Top MNCs
  • Package of Software Developer in Product Based Companies starts from 10LPA

Live Sessions

Live Sessions by Expertise Trainers and Access of Recorded Session is also available

Live Projects

Get a chance to work on Industry Oriented Projects to implement your learning

24*7 Support

24*7 Mentorship Support available for all Students to clear all of your doubts

Opportunities

REGex provides Internship / Job opportunities to the best Students in different Companies.

Our Students Placed In

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Course Content

● Flow charts
● Getting started
● Operators, Conditions and Loops
● Functions, Variables and their scope

● Patterns 1
● Arrays, Searching and Sorting
● Strings and 2D Arrays

● OOPs Concept
● Pointers
● Dynamic Allocation & Recursion
● Time Complexity

  • Setting up the environment
  • Jupyter NoteBook
  • Know about Importance of Competitive Programming
  • Key to get a JOB in Product Based Company, Start preparing for it
  • Data structures and abstract data types
  • What is an array data structure
  • Arrays related interview questions
  • Linked list data structure and its implementation
  • Stacks and queues
  • Related interview questions
  • Algorithmic Thinking, Peak Finding
  • Models of Computation, Python Cost Model, Document Distance
  • What are binary search trees
  • Practical applications of binary search trees
  • Problems with binary trees
  • Binary Search Trees
  • BST Sort
  • Balanced trees: AVL trees and red-black trees
  • AVL Trees, AVL Sort
  • Graph
  • Insertion Sort, Merge Sort
  • Heaps and Heap Sort
  • Counting Sort
  • Radix Sort
  • Lower Bounds for Sorting and Searching
  • Associative arrays and dictionaries
  • How to achieve O(1) constant running time with hashing
  • Ternary search trees as associative arrays
  • Hashing with Chaining
  • Simulation Algorithms
  • Table Doubling, DNA Sequence Matching
  • Integer Arithmetic
  • Karatsuba Multiplication
  • Square Roots
  • Newton’s Method
  • Shortest path algorithms
  • Dijkstra’s algorithm
  • Speeding up Dijkstra
  • Bellman-Ford algorithm
  • What are spanning trees
  • Kruskal Algorithm
  • Sorting algorithms
  • Bubble sort, selection sort and insertion sort
  • Quicksort and merge sort
  • Non-comparison based sorting algorithms
  • Counting sort and radix sort
  • Memoization, Subproblems, Guessing, Bottom-up; Fibonacci, Shortest Paths
  • Parent Pointers; Text Justification, Perfect-Information Blackjack
  • String Subproblems, Pseudo Polynomial Time.
  • Parenthesization, Edit Distance, Knapsack
  • Computational Complexity
  • Algorithms Research Topics
  • String Subproblems, Pseudo Polynomial Time.
  • Parenthesization, Edit Distance, Knapsack
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