Social Networks Course | IIT Ropar | Prof. Sudarshan Iyengar | NPTEL
Course Details
| Exam Registration | 7730 |
|---|---|
| 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 | 18 Apr 2026 IST |
| NCrF Level | 4.5 — 8.0 |
Unlock the Secrets of Our Interconnected World: A Course on Social Networks
In today's digital age, our world is a vast, intricate web of connections. From friendships and professional collaborations to the structure of the internet itself, we are surrounded by complex networks. Understanding these structures is no longer just an academic pursuit—it's a crucial skill for navigating the modern world. A new, comprehensive online course offered by the prestigious Indian Institute of Technology Ropar (IIT Ropar) makes this fascinating field accessible to everyone.
Taught by the renowned Prof. Sudarshan Iyengar, this 12-week undergraduate-level course, "Social Networks," delves deep into the science behind the connections that shape our society, technology, and economy.
Meet Your Instructor: Prof. Sudarshan Iyengar
Learning from an expert is key, and this course is led by one of the best. Prof. Sudarshan Iyengar, an Associate Professor in the Computer Science and Engineering department at IIT Ropar, brings a wealth of knowledge and a passion for teaching to this program.
- Academic Excellence: Holds a Ph.D. from the elite Indian Institute of Science (IISc).
- Award-Winning Educator: Known for his novel teaching methodologies, he has delivered over 350 popular science talks to audiences ranging from high school students to advanced graduates.
- Proven Online Pedagogy: Has created over 100 hours of online lectures that have successfully reached lakhs of students across the globe.
- Research Expertise: His research interests include Data Sciences, Social Computing, Social Networks, Collective Intelligence, Crowdsourced Technologies, and Secure Computation, making him the perfect guide for this subject.
What is This Course About?
The "Social Networks" course is designed to decode the complexity of the networks that envelop us. We interact with networks daily: friendship circles, online platforms like Facebook and Twitter, the World Wide Web, and transportation systems. These networks, when represented as graphs, hold a treasure trove of hidden patterns and insights.
This course, often termed Social Network Analysis (SNA), employs tools from graph theory, sociology, and game theory to reveal surprising secrets about how information spreads, how communities form, and why certain trends go viral. Whether you're a computer science student, a professional in marketing or sociology, or simply a curious learner, this course will change how you see the world.
Who Should Enroll?
INTENDED AUDIENCE: Any Interested Learners. While the course is set at an undergraduate level, particularly beneficial for Computer Science and Engineering students, it is structured to be engaging and understandable for anyone with an interest in networks, data, and human behavior. No prior specialized knowledge is required.
Detailed 12-Week Course Layout
Here’s a week-by-week breakdown of what you will learn, providing a clear roadmap for your journey into network science.
| Week | Topic |
|---|---|
| Week 1 | Introduction |
| Week 2 | Handling Real-world Network Datasets |
| Week 3 | Strength of Weak Ties |
| Week 4 | Strong and Weak Relationships (Continued) & Homophily |
| Week 5 | Homophily Continued and Positive / Negative Relationships |
| Week 6 | Link Analysis |
| Week 7 | Cascading Behaviour in Networks |
| Week 8 | Link Analysis (Continued) |
| Week 9 | Power Laws and Rich-Get-Richer Phenomena |
| Week 10 | Power Law (contd..) and Epidemics |
| Week 11 | Small World Phenomenon |
| Week 12 | Pseudocore (How to go viral on web) |
Key Concepts You Will Master
- Graph Theory Fundamentals: Learn to model real-world systems as networks.
- The Strength of Weak Ties: Discover why casual acquaintances can be more valuable than close friends for job opportunities and information flow.
- Homophily: Understand the principle of "birds of a feather flock together" in social networks.
- Link Analysis & Ranking: Uncover the algorithms (like PageRank) that power search engines.
- Viral Cascades & Epidemics: Model how information, trends, and even diseases spread through a population.
- Power Laws: Explore why a few nodes (like influencers) hold most of the connections in a network.
- Small World Phenomenon: Grasp the famous "six degrees of separation" concept.
- Going Viral: Apply your knowledge to understand the mechanics behind viral web content.
Recommended Textbooks
To supplement the video lectures, the course recommends two seminal texts in the field. Notably, one is available for free, ensuring the course remains accessible.
- Networks, Crowds and Markets by David Easley and Jon Kleinberg, Cambridge University Press, 2010 (available for free download).
- Social and Economic Networks by Matthew O. Jackson, Princeton University Press, 2010.
Why Enroll in This Social Networks Course?
This isn't just another online class. It's a chance to learn a critical, interdisciplinary skill set from a top-tier IIT professor at no cost. The ability to analyze and interpret networks is invaluable in fields like data science, marketing, public policy, cybersecurity, and sociology. By the end of 12 weeks, you will have a powerful lens to analyze the connected structures that define our digital and physical lives.
Ready to map the connections that matter? Enroll today and start your journey into the fascinating science of Social Networks.
Enroll Now →