Read the constraints
Translate input limits into a viable algorithm, and know when brute force is enough and when it is not.
ALGORITHMS & CONTEST STRATEGY
Competitive Programming.
To Crack Top Product Companies
Go beyond familiar DSA problems. Learn the algorithmic patterns, contest strategy and discipline to solve unfamiliar challenges under time pressure.
- Contest foundations
- Algorithmic patterns
- Contest strategy
ENQUIRE ABOUT THE COURSE
Your next chapter
Your next chapter
starts here.
Tell us a little about yourself.
Complete your syllabus request in the open window.
YOUR STARTING POINTDSA fundamentals
YOUR ROADMAP11 learning modules
COURSE DURATIONBatch-specific
YOUR LEARNING MODEClassroom or live
A FOUNDATION THAT TAKES YOU FURTHER
Understand the problem.
Own the solution.
Build more than familiarity with syntax. Learn how to approach an unfamiliar problem, reason about your choices, and turn your thinking into working code.
Know your DSA? Time to compete.
For students comfortable with C++ and core data structures who want to solve harder, unfamiliar problems on Codeforces and in contests.
Recognise the pattern
Apply reusable approaches, from binary search on the answer to segment trees and DP, to problems you have never seen.
Compete with consistency
Build speed and reasoning through practice contests, then upsolve to turn every miss into progress.
YOUR LEARNING ROADMAP
One concept leads
to the next breakthrough.
Move from contest foundations to the patterns behind faster solutions. Build the algorithmic thinking to understand, debug and improve code—even when AI helps write it.
FOUNDATIONS FOR THE AI ERA
Stronger fundamentals. Smarter use of AI.
AI can help you write code. Programming knowledge and logical thinking help you ask better questions, spot incorrect assumptions, debug generated code and judge a solution’s efficiency. Learn the fundamentals so you can build with AI and understand the result.
- Reason before you prompt
- Validate the output
- Own your solution
Your complete learning roadmap.
Download syllabus
Keep the module breakdown, practice assignments and learning outcomes.
Suggested curriculum. Confirm the current batch syllabus, module allocations and total duration with an advisor.
01 Standard Template Library (STL)
- Introduction to STL
- Containers and Iterators
- Vectors
- Lists
- Pairs
- Stacks
- Queues
- Priority Queues
- Sets
- Multisets
- Maps
- Unordered Maps
- Custom Comparators
- STL-Based Problem Solving
Put it into practice
Solve a problem set using STL containers and custom comparators.
What you’ll take away
Write fast, concise solutions with the STL.
02 Mathematics for Competitive Programming
- Mathematical Foundations
- Probability
- Conditional Probability
- Expected Value
- Linearity of Expectation
- Matrix Operations
- Matrix Multiplication
- Matrix Exponentiation
- Fast Exponentiation
- Modular Arithmetic
- Modular Exponentiation
- Big Integers
- Mathematical Problem-Solving Techniques
Put it into practice
Solve problems using modular arithmetic and matrix exponentiation.
What you’ll take away
Apply mathematical techniques to contest problems.
03 Number Theory
- Prime Numbers
- Prime Factorization
- Sieve of Eratosthenes
- LCM and GCD
- Euclidean Algorithm
- Extended Euclidean Algorithm
- Euler's Totient Function
- Wilson's Theorem
- Fermat's Little Theorem
- Fermat's Theorem
- Modular Multiplicative Inverse
- Chinese Remainder Theorem (CRT)
- Linear Diophantine Equations
- Matrix Exponentiation
- Number Theory Problems
Put it into practice
Solve a graded set of prime, GCD and modular inverse problems.
What you’ll take away
Recognise and apply number theory patterns.
04 Combinatorics and Counting Techniques
- Fundamental Principles of Counting
- Permutations and Combinations
- Factorials
- Binomial Coefficients
- Pascal's Triangle
- Catalan Numbers
- Birthday Paradox
- Pigeonhole Principle
- Inclusion-Exclusion Principle
- Counting Arrangements
- Combinatorial Problem Solving
Put it into practice
Solve counting problems using combinatorics and inclusion-exclusion.
What you’ll take away
Count arrangements efficiently and correctly.
05 Segment Trees and Fenwick Trees
- Introduction to Range Query Problems
- Segment Tree Construction
- Range Sum Queries
- Range Minimum and Maximum Queries
- Point Updates
- Range Updates
- Lazy Propagation
- Fenwick Trees (Binary Indexed Trees)
- Prefix Sum Queries
- Update Operations
- Time Complexity Analysis
- Optimized Subarray Algorithms
- Range Query Problem Solving
Put it into practice
Implement segment trees and Fenwick trees for range queries.
What you’ll take away
Answer range queries and updates efficiently.
06 Advanced Graph Algorithms
- Graph Representation
- Adjacency Lists
- BFS and DFS
- Multi-Source BFS
- 0-1 BFS
- Shortest Path Algorithms
- Dijkstra's Algorithm
- Bellman-Ford Algorithm
- Floyd-Warshall Algorithm
- Disjoint Set Union (DSU)
- Union by Rank
- Path Compression
- Minimum Spanning Trees
- Kruskal's Algorithm
- Strongly Connected Components
- Kosaraju's Algorithm
- Topological Sorting
- Directed Acyclic Graphs (DAGs)
- Bipartite Graphs
- Advanced Graph Problems
Put it into practice
Solve shortest path, MST and SCC problems.
What you’ll take away
Choose the right graph algorithm for each problem.
07 Advanced Tries and String-Based Problem Solving
- Trie Data Structure
- Trie Node Implementation
- Insertion
- Searching and Deletion
- Prefix Searching
- Word Frequency Problems
- Binary Tries
- Bitwise XOR Problems
- Maximum XOR Pair
- Trie-Based Optimization
- Time and Space Complexity Analysis
- Advanced Interview Problems Using Tries
Put it into practice
Implement tries and solve maximum XOR problems.
What you’ll take away
Solve string and bitwise problems with tries.
08 Dynamic Programming on Trees and Graphs
- Introduction to Tree DP
- Subtree-Based DP
- DFS-Based Dynamic Programming
- DP on Trees
- Tree Rerooting Techniques
- Dynamic Programming on Directed Acyclic Graphs
- Topological Order-Based DP
- Longest Path in DAG
- State Transitions
- Memoization
- Tabulation
- AtCoder Educational DP Contest Problems
Put it into practice
Solve tree DP and DAG DP problems from the AtCoder DP contest.
What you’ll take away
Apply dynamic programming on trees and graphs.
09 Digit DP and Rolling DP
- Introduction to Digit Dynamic Programming
- Digit-Based State Representation
- Tight Constraints
- Digit Sum Problems
- Counting Numbers Within a Range
- Digit DP
- Introduction to Rolling DP
- Space Optimization in Dynamic Programming
- Previous and Current State Optimization
- 1D and 2D DP Space Optimization
- Advanced Digit DP Problems
Put it into practice
Solve digit DP problems and space-optimise DP solutions.
What you’ll take away
Count numbers in ranges and reduce DP memory.
10 Advanced Dynamic Programming Algorithms
- Understanding DP States and Transitions
- 0/1 Knapsack
- Unbounded Knapsack
- Subset Sum
- Partition Problems
- Binary Search Optimization for LIS
- Matrix Chain Multiplication
- Interval DP
- Memoization
- Tabulation
- Time and Space Complexity Optimization
- Advanced Placement-Oriented DP Problems
Put it into practice
Solve knapsack, LIS and interval DP problems.
What you’ll take away
Define DP states and transitions confidently.
11 Greedy Algorithms and Optimization Techniques
- Introduction to Greedy Algorithms
- Greedy Choice Property
- Optimal Substructure
- Sorting-Based Greedy Techniques
- Activity Selection
- Interval Scheduling
- Fractional Knapsack
- Job Sequencing
- Priority Queue-Based Greedy Problems
- Greedy Algorithms on Arrays
- Greedy vs Dynamic Programming
- Identifying Greedy Approaches
- Proving Greedy Correctness
- Exchange Arguments
- Competitive Programming Problems
Put it into practice
Solve scheduling and interval problems greedily.
What you’ll take away
Recognise and prove greedy approaches.
Takeaway from the course
- Codeforces
- CSES
- Combinatorics
- Contests
- Cheat sheets
- ACM-ICPC
- Advanced Data structures
- Dynamic programming
- Algorithms
PUT THE IDEAS TO WORK
Make the concepts
something you can show.
Go beyond isolated problems. These project ideas turn your contest techniques into reusable, tested code you can build on and explain.
A → B → D → EPath cost: 9
PROJECT IDEA · CONNECTED THINKING
Shortest path solver
Model a weighted graph, find the cheapest path with Dijkstra, and know which shortest-path algorithm fits the constraints.
Segment tree · DSU · SieveTested ✓
PROJECT IDEA · UNDER THE HOOD
Algorithm toolkit
Build and test your own library of segment trees, DSU and number theory utilities, ready to use in your next contest.
Start → Explore → FinishPath found ✓
PROJECT IDEA · GRID THINKING
Grid path solver
Explore a grid with BFS, avoid blocked cells, and find the shortest route. A classic contest pattern, one layer at a time.
Upsolving journalProgress ✓
PROJECT IDEA · DELIBERATE PRACTICE
Contest solution portfolio
Keep a record of contest solutions and upsolves, with the approach and complexity behind each one.
Pattern → Prefix → Match2 matches ✓
PROJECT IDEA · FIND THE SIGNAL
Pattern matcher
Find every occurrence of a pattern in linear time, and compare KMP with rolling hashes on large inputs.
Illustrative project previews. Your mentor will confirm project scope and review criteria for your batch.
HOW THE LEARNING COMES TOGETHER
Understand it.
Then make it your own.
A learning rhythm that connects the concept, the code and your reasoning. Here’s how you can turn each new topic into a skill.
See the why
Walk through the idea and trace examples. Understand when an approach works and where it falls short.
Write the code
Solve timed problem sets and practice contests. Debug, test edge cases, and upsolve what you missed.
Talk it through
Explain your approach, compare alternatives, and connect your solution to time and space complexity.
Ask your advisor about assignment reviews, doubt support, recordings and practice contest inclusions for your chosen batch.
FIND YOUR LEARNING ENVIRONMENT
Same ambition.
Your way to learn.
Choose the environment that suits your routine. Our advisors can help you compare current batches, schedules and support.
Learn in a classroom.
Bring your questions to class, learn alongside peers, and build a routine around in-person sessions.
Explore Noida & NSP centres Find a classroom batchJoin from where you are.
Attend live sessions remotely. Find a batch whose timing and learning support work for your day.
Live sessions · learn remotely Explore live batches
UP TO100%SCHOLARSHIP
CAST · YOUR OPPORTUNITY TO LEARN
Apply for CAST
Your ambition. A scholarship to match.
Apply for CAST — the Coding Blocks Aptitude and Scholarship Test — and earn a scholarship of up to 100% on course fees.
Available for classroom and Live interactive courses, including Sampoorna. Awards are subject to the test’s eligibility and award terms.
YOUR CENTRE. YOUR SCHEDULE.
Your schedule. Your batch.
Choose NSP or Noida, then find the weekday or weekend schedule that fits you.
Competitive Programming at NSP, Delhi
No upcoming batches
See the centre
No batches are currently listed for this selection. Contact our team about the next intake.
Talk to an advisor
Your selected batch
A LITTLE CLARITY
Good questions.
Clear answers.
What should I know before joining?
The suggested curriculum assumes you are comfortable with C++ and core data structures. It starts with contest foundations such as complexity, fast I/O and STL before moving into advanced patterns. If you are new to DSA, start with DSA using C++. Tell your advisor about your experience to check your starting point.
How do I choose between classroom and live learning?
Choose classroom learning if you prefer an in-person routine and peer interaction. Live learning lets you attend remotely. Ask about current Competitive Programming batch availability, timings and support before choosing your mode.
What will I practise and build?
The suggested roadmap includes topic exercises, practical assignments, timed problem sets, practice contests and project ideas such as a contest solution portfolio and an algorithm toolkit. Your mentor will confirm project scope, review criteria and the curriculum for your batch.
What are the course duration, timings and fees?
These depend on your selected batch and learning mode. Contact an advisor for the current start date, class schedule, total duration and fees.
Who will teach my batch, and what support is included?
Mentor allocation and support are confirmed with your selected batch. Ask your advisor about doubt sessions, assignment reviews, recording access and practice contest inclusions before enrolling.
Real people. Real milestones.
Our torchbearers.
Just getting started.
Meet Coding Blocks learners whose practice and persistence led to opportunities at leading companies.
Aditya
Iti Jain
Simarpreet Sikka
Vishesh
Jashpreet Malhotra
Walmart
Sahil Bansal
Shervil Gupta
Ashanka Saha
Sandipan Dutta
Lavisha Malik
Manali Biswas
Mohit K.
CODING BLOCKS CERTIFICATE
Skills you’ve built.
An achievement to show.
Celebrate the work you put into competitive programming with a Coding Blocks certificate of completion. Add it to your portfolio and share a milestone in your learning journey. Ask your advisor about the completion criteria for your batch.
-
A record of your completed program
-
A meaningful addition to your portfolio
-
A milestone to share with your network
OUR CLASSROOM CENTRES
Find your classroom.
Right here in Delhi NCR.
Learn with us in Noida or Netaji Subhash Place, Delhi. Find the centre that fits your commute, get directions and come meet the team.
Noida
Sector 2 · Uttar Pradesh
VISIT US
First Floor, A-73, Sector 2,
Noida, Uttar Pradesh 201301
Noida, Uttar Pradesh 201301
CONTACT NUMBER
+91 99995 79111 — call the Noida centre
Near Sector 15 Metro
Get directions to the Noida centre (opens in a new tab)
NSP, Delhi
Netaji Subhash Place · Pitampura
VISIT US
4th Floor, PP Tower, Tower B,
Netaji Subhash Place, Delhi 110034
Netaji Subhash Place, Delhi 110034
CONTACT NUMBER
+91 99993 21553 — call the NSP, Delhi centre
Call us to plan your visit
Get directions to the NSP, Delhi centre (opens in a new tab)
Your next breakthrough
starts with deliberate practice.
Let’s find a Competitive Programming batch that fits where you are and where you want to go.