Want to start competitive programming but don't know where to begin? I've been there. Here's how I went from zero to solving 1500+ problems and reaching Specialist on Codeforces.

Step 1: Choose Your Language – Start with C++ for speed and STL power. Learn basic syntax, loops, conditionals, arrays, and strings.

Step 2: Master the Basics – Solve 50-100 easy problems on Codeforces, AtCoder, or CSES to build confidence with I/O, logic, and debugging.

Step 3: Learn Problem-Solving Patterns – Study sorting, searching, two pointers, prefix sums, and greedy approaches. These appear in 80% of beginner problems.

Step 4: Join Contests – Participate in Codeforces Div 3/4 contests weekly. Even if you solve just one problem, you're learning under pressure.

Check out my Code Drive repository for categorized practice problems and solutions to kickstart your journey.

Preparing for ICPC requires strategy, teamwork, and consistent practice. As someone who ranked 39th in ICPC Dhaka Regional 2024 and 26th in AUST IUPC 2025, here's my proven roadmap.

Build Strong Foundations: Master graph algorithms (BFS, DFS, Dijkstra, MST), dynamic programming (knapsack, LCS, subset sum), number theory (GCD, modular arithmetic, prime sieves), and data structures (segment trees, DSU, heaps).

Weekly Mock Contests: Simulate real contest conditions—5 hours, 3 team members, one computer. Practice problem division: assign graph/DP/math problems to specialists.

Analyze Past Problems: Study previous ICPC regional problems. Identify recurring patterns like shortest paths, bipartite matching, and combinatorics.

Team Communication: Hold post-contest retrospectives. Discuss what went wrong, time management mistakes, and debugging strategies.

Need mentorship? I offer personalized ICPC coaching for KUET students and regional teams.

Data structures and algorithms are the backbone of competitive programming. Here's how I mastered them systematically.

Phase 1: Linear Data Structures – Arrays, linked lists, stacks, queues. Understand when to use each and implement from scratch once.

Phase 2: Trees and Graphs – Binary trees, BST, heaps, graph representations (adjacency list/matrix), traversal algorithms (BFS, DFS).

Phase 3: Advanced Structures – Segment trees for range queries, disjoint set union (DSU) for connectivity, tries for string problems, fenwick trees for prefix sums.

Phase 4: Algorithm Techniques – Divide and conquer (binary search, merge sort), dynamic programming (top-down and bottom-up), greedy algorithms, and backtracking.

Practice Resources: CSES Problem Set, AtCoder Educational DP Contest, Codeforces Edu section, and my Code Drive solutions.

Pro tip: Don't just read theory, implement every data structure and solve 10+ problems per topic before moving on.

While competitive programming builds problem-solving skills, understanding core CSE concepts like OOP and DBMS is essential for software development and academic success.

Object-Oriented Programming (OOP): Learn the four pillars—encapsulation, inheritance, polymorphism, and abstraction. Practice with C++ or Java by building small projects like a library management system or banking application.

Database Management Systems (DBMS): Understand relational databases, SQL queries (joins, aggregations, subqueries), normalization (1NF to BCNF), and transaction management (ACID properties). Practice on MySQL or PostgreSQL.

Operating Systems: Study process scheduling, memory management, deadlocks, and file systems. These concepts appear in technical interviews.

Computer Networks: Learn OSI layers, TCP/IP, HTTP/HTTPS, DNS, and socket programming basics.

I offer tutoring sessions for KUET juniors and school/college students on these topics. Whether you need help with assignments, exam prep, or building foundational understanding, reach out.