Competitive Programming Course: Learn Algorithms with IIT Gandhinagar Prof
Course Details
| Exam Registration | 956 |
|---|---|
| Course Status | Ongoing |
| Course Type | Elective |
| Language | English |
| Duration | 12 weeks |
| Categories | Computer Science and Engineering |
| Credit Points | 3 |
| Level | Undergraduate |
| Start Date | 19 Jan 2026 |
| End Date | 10 Apr 2026 |
| Enrollment Ends | 02 Feb 2026 |
| Exam Registration Ends | 20 Feb 2026 |
| Exam Date | 17 Apr 2026 IST |
| NCrF Level | 4.5 — 8.0 |
Your 12-Week Journey to Mastering Competitive Programming
Are you an undergraduate computer science student looking to deepen your algorithmic knowledge and take your coding skills to the next level? Perhaps you're aiming to crack prestigious coding competitions like the International Collegiate Programming Contest (ICPC) or prepare for rigorous technical interviews at top tech companies. If so, a structured approach is key. This article outlines a comprehensive 12-week course, designed by Prof. Neeldhara Misra of IIT Gandhinagar, that provides the perfect roadmap from foundational concepts to advanced problem-solving techniques.
About the Course and Instructor
This course, Getting Started with Competitive Programming, is meticulously crafted to bridge the gap between theoretical algorithm knowledge and practical, competition-ready implementation. It is led by Prof. Neeldhara Misra, an Assistant Professor of Computer Science and Engineering at IIT Gandhinagar. Her expertise lies in the design and analysis of efficient algorithms for complex problems in graph theory, optimization, and beyond, making her an ideal guide for this journey.
The course focuses on algorithm design, modeling, and implementation. Each lecture is centered on specific problems that illuminate a core algorithmic technique, ensuring you not only understand the theory but also learn how to apply it effectively under time constraints.
Who Should Take This Course?
This course is specifically intended for:
- Undergraduate students who have completed a basic data structures and algorithms course.
- Coders who want to solidify their understanding of algorithmic techniques through practice.
- Aspiring participants of coding competitions (ICPC, CodeChef, Codeforces).
- Students preparing for technical interviews at major technology companies.
Prerequisites & Industry Relevance
To succeed, you should be familiar with:
- Data Structures and Algorithms fundamentals.
- A programming language, ideally C++ or Python, due to their prevalence in competitive programming.
The skills honed in this course are directly applicable to the hiring processes of most leading tech firms. Companies like Facebook (Meta), Google, Amazon, Apple, and Microsoft heavily rely on algorithmic problem-solving tests to assess candidate competence. This course serves as an excellent preparation ground for such challenges.
Detailed 12-Week Course Layout
Follow this week-by-week syllabus to build your expertise systematically.
| Week | Core Topic | Focus Area |
|---|---|---|
| Week 1 | Sorting and Searching | Binary search, efficient sorting algorithms and their applications. |
| Weeks 2 & 3 | Greedy Algorithms | Problem-solving with locally optimal choices, proof techniques. |
| Week 4 | Disjoint Set Union (DSU) | Union-Find data structure with path compression for connectivity problems. |
| Week 5 | Minimum Spanning Tree (MST) | Kruskal’s and Prim’s algorithms. |
| Week 6 | Shortest Paths | Dijkstra's algorithm, Bellman-Ford, and Floyd-Warshall. |
| Weeks 7 & 8 | Network Flows & Divide and Conquer | Max-flow min-cut theorem, Ford-Fulkerson method; classic D&C paradigms. |
| Weeks 9 - 12 | Dynamic Programming (DP) | An extensive four-week deep dive into DP, covering memoization, tabulation, and advanced state definition for complex problems. |
Essential Books and Resources
Complement your learning with these authoritative texts:
- Algorithms by Jeff Erickson (Freely available online) - A great theoretical companion.
- Algorithms Illuminated by Tim Roughgarden - Excellent for building intuition.
- Algorithm Design by Jon Kleinberg and Éva Tardos - A comprehensive textbook on design techniques.
- Introduction to Algorithms (CLRS) by Cormen et al. - The classic reference book.
- Competitive Programming 4 by Steven Halim and Felix Halim - A must-have practical guidebook for contestants.
- Guide to Competitive Programming by Antti Laaksonen - Another fantastic resource focused on contest preparation.
Your Action Plan to Get Started
1. Assess Your Foundation: Ensure you are comfortable with basic data structures (arrays, linked lists, trees, graphs) and syntax of C++/Python.
2. Follow the Schedule: Dedicate time each week to the topic. Understand the concept, then solve progressively harder problems on platforms like Codeforces, LeetCode, or CodeChef.
3. Practice Relentlessly: Competitive programming is a skill built through consistent practice. Aim to solve a variety of problems for each technique.
4. Learn from Solutions: If stuck, don't just read the answer. Understand the thought process behind the optimal solution.
5. Participate in Contests: Apply your learning in weekly online contests. The time pressure and unpredictability are part of the training.
Embarking on this 12-week journey with the structure provided by Prof. Misra's course outline will transform your approach to algorithmic problems. It moves you from knowing algorithms to wielding them effectively—a distinction that defines success in both competitive programming and high-stakes technical careers. Start today, be consistent, and watch your problem-solving abilities soar.
Enroll Now →