Best Competitive Programming Course Online by Coding Ninjas: Fee, Duration, How to Apply

Quick Facts

particular	details
Medium of instructions English, Hindi	Mode of learning Self study, Virtual Classroom	Mode of Delivery Video and Text Based

Course overview

The Competitive Programming certification course is a complete online course available in both media - Hindi and English language. The Competitive Programming training will prepare the candidate for the ICPC, Hackercups, and many more. The course is accompanied by dedicated placement assistance support that will make the candidate more effective for his or her future career. This particular course will help the candidate in enhancing their respective cognitive and problem-solving skills in the field of programming. The candidate will get Competitive Programming certification at the end of the completion of the programme.

Course and certificate fees

certificate availability

Yes

certificate providing authority

Coding Ninjas

Who it is for

Following candidates can opt for the course -

The individual who wants to upgrade their skills in coding and wants to gain experience should opt for this particular online course.

Eligibility criteria

Education

As for the fundamental knowledge, the candidate needs to have a good fundamental knowledge of programming, basic mathematics, and the implementation of data structures for applying in the Competitive Programming certification course.

Certification qualifying details

The candidate can attain the Competitive Programming certification in two kinds. Mainly, if the candidate passes the course with a minimum grade of 60% then he will be awarded a course completion certificate but if the candidate scores 90% or above then he will get the certificate of excellence.

What you will learn

C++ Knowledge of python

As the Competitive Programming programme will end, the candidates will learn the following concepts -

During the course, the candidates would learn to solve hard coding problems like in ACM-ICPC.
Python programming will be taught to the students as the fundamentals.
The candidate can easily solve the OOPs content’s problems and case studies.
The whole course is based on making students understand the hard programming languages.
The Candidate mainly attains the cognitive and problem-skills that will help them in their academics.
Different mathematical theories, line number theory, computational geometry will be implemented in the course.
C++ must be taught at the end of the course that will give the student more effective learning about the course.

The syllabus

Introduction to Programming

Basics of Programming

Flowcharts
- Introduction to flowcharts,
- Decision-making using flowcharts,
- Loops,
- Example problems
Variables and Data Types
- First program,
- Variables and data types,
- Taking input,
- How data is stored in memory,
- Arithmetic Operators
Conditional Statements
- Introduction to If else,
- Relational and logical operators,
- Nested conditionals

Loops and Functions

While Loops
- While loops,
- Flow of execution of statements in while loop,
- Example problems using while loop
Patterns
- Introduction to patterns,
- Basic Patterns,
- Square Patterns,
- Triangular Patterns,
- Character Patterns,
- Reverse Triangle,
- Inverted patterns,
- Isosceles triangles
For Loops
- For loops,
- Break and Continue, increment - decrement operators
Functions
- Introduction to functions,
- Working of function calling,
- Variables and its scope,
- Pass by value

Arrays

Introduction to Arrays
- Introduction to arrays,
- How arrays are stored in memory,
- Passing arrays to functions
Searching and Sorting
- Understanding Binary Search,
- Selection sort,
- Bubble sort,
- Insertion sort,
- Merging two sorted arrays

Strings and 2D Arrays

Strings
- Introduction to strings, storage of strings, and their inbuilt functions
2D Arrays
- 2D arrays,
- Storage of 2D arrays,
- Example problems using 2D Arrays

Data Structures & Algorithms

Problem Solving Techniques

Recursion
- Introduction to recursion,
- Principle of mathematical induction,
- Fibonacci numbers,
- Recursion using arrays,
- Recursion using strings,
- Recursion using 2D arrays
Time and Space Complexity
- Order complexity analysis,
- Theoretical complexity analysis,
- Time complexity analysis of searching and recursive algorithms,
- Theoretical space complexity,
- Space complexity analysis of merge sort

Object Oriented Programming

Basics of OOPS
- Introduction to OOPS,
- Creating objects,
- Getters and setters,
- Constructors and related concepts,
- Inbuilt constructor and destructor,
- Example classes
Advance Concepts of OOPS
- Static members,
- Function overloading and related concepts,
- Abstraction,
- Encapsulation,
- Inheritance,
- Polymorphism,
- Virtual functions,
- Abstract classes,
- Exception handling

Linear Data Structures

Linked Lists
- Introduction to linked list,
- Inserting node in linked list,
- Deleting node from linked list,
- Midpoint of linked list,
- Merge two sorted linked lists, merge sort of a linked list,
- Reversing a linked list
Stacks and Queues
- Introduction to stacks, Stack using arrays,
- Dynamic Stack class,
- Stack using linked list,
- Inbuilt stack,
- Queue using arrays,
- Dynamic queue class,
- Queue using linked list,
- Inbuilt queue

Trees

Generic Trees
- Introduction to Trees,
- Making a tree node class,
- Taking a tree as input and printing,
- Tree traversals,
- Destructor for tree node class
Binary Trees
- Introduction to Binary Trees,
- Taking a binary tree as input and printing,
- Binary Tree traversals,
- Diameter of binary tree
Binary Search Trees
- Introduction to Binary Search Trees,
- Searching a node in BST,
- BST class,
- Inserting and Deleting nodes in BST,
- Types of balanced BSTs

Advanced Data Structures

Priority Queues
- Introduction to Priority Queues,
- Ways to implement priority queues,
- Introduction to heaps,
- Introduction to Complete Binary Trees and its implementation,
- Insert and Delete operations in heaps,
- Implementing priority queues,
- Heap sort,
- Inbuilt Priority Queue
Hashmaps
- Introduction to Hashmaps,
- Inbuilt Hashmap,
- Hash functions,
- Collision handling,
- Insert and Delete operation implementation in hashmap,
- Load factor,
- Rehashing
Tries
- Introduction to Tries,
- Making a Trie Node class,
- Insert,
- Search and Remove operation implementation in Tries,
- Types of Tries,
- Huffman Coding
Graphs
- Introduction to Graphs,
- Graph Terminology,
- Graph implementation,
- Graph Traversals (DFS and BFS),
- Weighted and Directed Graphs,
- Minimum Spanning Trees,
- Cycle Detection in Graphs,
- Kruskal's algorithm,
- Prim's Algorithm,
- Dijkstra's algorithm

Dynamic Programming

Introduction to Dynamic Programming
- Introduction to Memoization,
- Introduction to Dynamic Programming,
- Fibonacci numbers using recursion, memoization and dynamic programming
Applications of Dynamic Programming
- Longest Common Subsequence (LCS) using recursion, memoization and dynamic programming,
- Edit distance using recursion, memoization and dynamic programming,
- Knapsack problem using recursion, memoization and dynamic programming

Competitive Programming

Basics of Competitive Programming

Introduction to Competitive Programming
- Why Competitive Programming?,
- How To Approach A Problem In Contest,
- Various Types Of Errors
Basics of Recursion
- Introduction to Recursion,
- Recursion and PMI,
- Fibonacci Number,
- Recursion and Arrays
Time and Space Complexity Analysis
- Order Complexity Analysis,
- Theoretical Analysis,
- Linear Search time complexity,
- Insertion Sort time complexity,
- Selection Sort time complexity,
- Theoretical Analysis - Recursive Algorithms,
- Merge Sort Time complexity,
- Fibonacci Time Complexity Analysis,
- Space Complexity Analysis,
- Merge Sort Space Complexity Analysis,
- Fibonacci Space Complexity Analysis,
- Kadane's Algorithm
Language Tools
- STL - Data Structures,
- STL - Functions,
- Hussain Set,
- Voters List,
- Permutation & Palindrome
Searching & Sorting Applications
- Aggressive Cows, Inversion Count

Basic Problem Solving Skills used in Competitive Programming

Two Pointers and Sliding Window
- Working of two-pointers and sliding window technique,
- Intuition behind Two Sum Problem Max sum of k consecutive elements and Longest Substring with At Most Two Distinct Characters
Greedy Algorithms
- Introduction to Greedy Algorithms,
- Greedy Vs DP,
- Logic building for the problems like Fraction Knapsack and Activity Selection etc.
Sorting
- Introduction to Sorting Algorithms,
- Working of Sorting algorithms like Merge Sort, Quick Sort Counting Sort etc and A problem based on the Quickselect Algorithm
Binary Search
- Binary Search and its implementation details,
- Problems based on search on answer and problems based on search on input.

Applications of Recursion

Advanced Recursion
- Generating all subsets and all Permutations using recursion and Logic building of Combination sum Problem
Backtracking
- Introduction to Backtracking Algorithms,
- Recursion vs Backtracking and Logic behind popular problems like Rat in a Maze, N-Queens

Bit Manipulation and Number Theory

Bit Manipulation
- All basic bitwise operators like (OR, AND, NOT, XOR, Left Shift and Right Shift) and properties of each of these operators Common operations done using these operators(like Set ith bit, Count Set Bits)
Number Theory-I
- Checking whether a number is prime or not in sqrt(n) time Sieve algorithm,
- Segmented Sieve problem’s solution,
- Euclid’s algorithm,
- What are LDEs and how to solve them using Extended and Euclid’s algo
Number Theory-II
- Modular Arithmetic Properties,
- How to find Modular Inverse,
- How to find number of solutions of LDEs and Euler’s Totient Function
Number Theory-III
- Exponentiation and Modular Exponentiation Matrix Exponentiation,
- How to find Nth term of a recurrence relation using Matrix Exponentiation and How to find Nth term of Fibonacci Series
Number Theory-IV
- Non-Deterministic Primality Tests,
- Fermat's Theorem,
- Miller Rabin Test and its Deterministic Version,
- Wilson's Theorem and Chinese Remainder Theorem

Dynamic Programming and Disjoint Sets

Dynamic Programming 1
- Basics of Dynamic Programming(Introduction, Need) and Memoization vs Tabulation Method Optimization of recurrence relation (overlapping subproblem) into DP- Solution 2-dimensional DP Solution
Dynamic Programming II
- The intuition behind problems like LCS, LIS(How to build logic),
- Further Optimization of Dynamic Programming Solution using Segment tree or binary search Multidimensional(3D,4D) Dp Solution Conversion of DP-State into DP-Transition and vice-versa
Dynamic Programming III
- Algorithms based on Tree DP including Binary Lifting,
- Re-rooting(In-Out) DP,
- Algorithms based on Graph DP and Algorithms based on Digit DP
Disjoint Set
- Introduction to Disjoint Set Data-Structure,
- Need and Applications of DSU, find and Union Operation and union by Rank and Path Compression Technique

Trees

Tree-I
- Introduction to Trees(different terminologies related to tree, need of non-linear data structure, applications),
- Various Tree Traversal Techniques,
- N-ary vs Binary Tree and Concepts based on n-ary tree
Tree-II
- Introduction to Euler’s Tour,
- Technique(Construction and Properties),
- Introduction to Mo’s algorithm,
- Problems based on Tree Queries like Subtree Queries and Path Queries

Graphs

Graph-I
- Introduction and Basic terminologies of Graph,
- DFS and BFS,
- Finding Path Between Two Nodes,
- Detecting Cycle in Graph and Topological Sorting
Graph-II
- Minimum Spanning Trees,
- Kruskal Algorithm Prims Algorithm,
- Explaining Dijkstra Algorithm,
- Bellman-Ford Algorithm and Floyd Warshall Algorithm
Graph-III
- Bipartite Graph Test,
- Introduction & Applications of SCC,
- Tarjan's Algorithm for SCC and articulation points and Bridges-what are they how to find them

Combinatorics

Combinatorics-I
- Introduction to Combinatorics, revising Permutation and Combination,
- Combinatorics-nCr, nPr and Binomial coefficient etc
Combinatorics-II
- Catalan Number,
- Inclusion-exclusion,
- PigeonHole Principle and Application of Combinatorics Technique

Geometry

Geometry-I
- Introduction to Computational Geometry,
- Distance of a Point from a Line,
- Collinear Points,
- Intersection of Two line segment and Circle line intersection
Geometry-II
- Area of Polygon,
- Convex Hull- Algorithm & Applications

Game Theory

Game Theory
- Game theory-game states,
- Nim game and Sprague-Grundy theorem

Strings

Strings-I
- Strings Data Structure and their huge,
- Importance in CP Pattern Matching basics,
- Rabin-Karp Algorithm,
- Longest Prefix Suffix explanation and KMP & Z-Algorithm
Strings-II
- Manchester Algorithm and Introduction to Suffix Array,
- LCP Array

Tries

Tries
- Introduction to Trie Data Structure,
- Search,
- Insert & Deletion using Trie and Applications of Trie Data Structure

Range Query

Range Query-I
- Introduction to Range Query Data Structure Segment Tree
- i) Explaining use case
- ii) Showing implementation range query, point update, range update(Lazy Propagation)
Range Query-II
- Fenwick Tree
- i) Explaining use case
- ii) Showing implementation range query, point update, range update Sqrt Decomposition i) Explanation,
- Implementation Mo’s Algorithm i) Online Query ii) Offline Query

Bit Masking

Bit Masking
- Introduction to Bit Masking Its Usage(related to Dp) and Representing subsets,
- DP+Bitmasking Problems

Admission details

To enrol in the Competitive Programming online course, follow the following steps:

Step 1: Visit the web page to have information about the whole course highlights on https://www.codingninjas.com/competitive-programming-course

Step 2: The candidate can go for two options, either for “enrol now” or “try for free”.

Step 3: If the candidate is going with the enrolling now option, then the first login or register for registering.

Step 4: The portal will direct the candidate to the payment option and the candidate is enrolled in the programme.

Step 5: Candidates can even go with the try for a free option, after the free trial ends, they have to pay the fee in the end and the registration is done.

Evaluation process

The candidate needs to make timely submissions of the complete fifteen assignments for attaining certification at the end of the course.

How it helps

The main Competitive Programming certification benefits in terms of course curriculum and placement support that is given to the student during the course. High-level dedicated placement support and assistance are given to the candidates so that they can come into the limelight of the recruiters.