In today’s tech-driven world, strong problem-solving and competitive programming skills are essential for computer science students. To cultivate these abilities, we have integrated competitive programming into courses such as Problem Solving and Algorithmic Thinking (19CSE100) in semester 1 and 19CSE102 Computer Programming in semester 2. Students engage with Grade A problems on popular online judging platforms like Codeforces, Codechef, LeetCode, HackerRank as part of their lab exercises and classwork. For advanced courses like 19CSE212 Data Structures and Algorithms and 19CSE302 Design & Analysis of Algorithms, Leetcode and HackerRank were used for conducting online lab exams and lab exercises by providing a structured environment with features like custom problem creation, real-time code execution, and automated grading based on predefined test cases.
Kaggle provides a structured environment where faculty can host their own competition using a no-cost, self-service platform. With support from the Kaggle team, we prepare the data, write the problem statement, and set the competition terms. Once launched, Kaggle monitors the competition, scoring submissions in real time and awarding winners based on their performance. This practice immerses students in a real-world data science challenge, allowing them to experience the thrill and rigor of competitive problem-solving. By engaging in these contests, students gain exposure to large-scale data analysis, algorithm development, and performance optimization—all essential skills in the field of AI and machine learning. Additionally, being featured on Kaggle gives students visibility within the global data science community, helping them connect with professional data scientists and industry experts. For instance, in the Machine Learning course, a Kaggle competition was hosted, and students’ performance was evaluated by the Kaggle system.
Incorporating invited expert lectures and peer-led workshops has become an innovative practice in various courses, enriching students learning experiences. Invited talks by industry experts or academic leaders provide students with firsthand insights into cutting-edge developments, tools, and real- world applications, bridging the gap between theoretical knowledge and practical implementation. These sessions not only expose students to the latest trends but also offer networking opportunities with professionals. In parallel, senior students often conduct workshops on trending topics, fostering a peer- to-peer learning environment. Their ability to explain complex topics from a learner’s perspective makes these sessions especially valuable for juniors, helping clarify challenging concepts and ensuring that all students, regardless of their proficiency level, grasp key ideas. To enhance the course further, a peer-led workshop titled “Road to Machine Learning” was organized by senior students. This session promoted collaborative learning and critical thinking among students.
We follow a progressive approach by integrating research into elective courses, fostering a research mindset among students. As part of continuous assessment, students undertake research projects that align with the course objectives. These projects are structured with milestone-based submissions, guiding students through the various stages of the research pipeline. Starting from problem identification, students move on to conducting a thorough literature review, identifying research gaps, proposing novel solutions, implementing these solutions, performing performance evaluations, and finally, compiling their findings in the form of a research paper. Exceptional student groups often go on to submit and present their work at Scopus-indexed conferences, gaining exposure to the academic community.
Faculty maintain their course page in MS sharepoint to circulate to students and also to be visible to other peer faculty members to adopt it for their courses. This improves the visibility of innovative teaching practices which can help improve the overall teaching quality of the department.
Some sample course pages:
| Course | Course page |
|---|---|
| 19CSE205 Program Reasoning | Click Here |
| 19CSE102 Computer Programming | Click Here |
| 19CSE100 Problem Solving and Algorithmic Thinking | Click Here |
Faculty members have effectively utilized Slido, an interactive quiz maker, to enhance student engagement and interaction throughout course. Slido seamlessly integrates with PowerPoint, enabling instructors to create live polls, run quizzes, and facilitate real-time Q&A sessions, transforming traditional lectures into dynamic and interactive learning experiences. One of Slido’s standout features is its anonymous question submission, which encourages open participation.
Including DataCamp in courses strengthens practical skill development, enables objective assessment, and supports outcome-based, student-centered learning. The platform includes industry-relevant Python, R, and data science problems that reinforce practical application of concepts taught in class. It reinforces practical skills through hands-on coding exercises aligned with course outcomes.
Project-Based Learning (PBL) is an adopted active learning method in the department which is practiced for courses like Software Engineering, and electives fostering critical thinking, creativity, and problem-solving skills among students. A framework is designed to guide students through the process of identifying, analyzing, and refining their ideas into well-structured, solvable problem statements. By breaking down the ideation process into systematic steps, this approach students to think critically about the scope, feasibility, and relevance of their chosen problems, ensuring that their projects are grounded in realistic goals while still allowing for creativity and innovation. Dr. Jayaraj Poroor and Dr. Maya Menon who were part of CSE department in 2019 had published a research paper based on the innovative practice of project-based learning which was later adopted in courses like Software Engineering and some electives.
19CSE304 Foundations of Data Science course offers students a comprehensive understanding of the foundational concepts of data mining and machine learning. By exploring the types, motivations, and challenges associated with machine learning, students gain insights into supervised and unsupervised learning algorithms that are central to the data mining process. The course includes hands-on Python lab sessions where students build and evaluate predictive models using real-world data, seamlessly bridging theory with practice.
Some faculty members have the practice of using flipped classroom which is an instructional model where the traditional teaching approach is reversed. In this model, students engage with learning materials—such as video lectures, or readings—before class at their own pace, outside the classroom. The flipped classroom technique involved shifting traditional lectures outside the classroom by using video lectures and online materials for students to engage with before class. During in-person sessions, students work on problem-solving activities and participate in discussions to deepen their understanding. This approach maximized classroom time for practical applications and addressing misconceptions. The goal is to foster active learning and critical thinking, allowing students to tackle complex algorithm design problems collaboratively.
Sample course pages:
Object Oriented Programming Algorithm
As part of the Soft Skills course, we have introduced the Student Social Responsibility (SSR) project, an innovative evaluation scheme designed to inspire students to become socially responsible citizens. The SSR project encourages students to form teams and engage in community-oriented initiatives, such as interacting with underprivileged children, supporting cancer patients, and collaborating with schools in remote areas. Students also participate in meaningful causes such as blood donation, nature conservation, women empowerment, and knowledge sharing with younger students.
Established in 2013, Amrita Live-in-Labs® is a multidisciplinary experiential learning program that facilitates the research, development, and deployment of sustainable solutions for current challenges faced by rural communities in India. The program is designed to engage participants in a mutual learning and sharing experience by breaking classroom and lab barriers to implement theoretical knowledge to address real-world problems. The program allows participants to study, observe, and interact with rural populations while living in rural communities to gain a better understanding of various challenges. The program brings together Amrita students and faculty – in conjunction with students and faculty from international universities – to form multidisciplinary teams that will spend two weeks to six months in Indian villages.
Cyber Security Training
One such initiative is Cyber Security Training, where students stay back in the evening and actively engage in additional projects under faculty guidance. The training sessions are also handled by Mr. Vipin P, Managing Director, Traboda Cyberlabs. This training covers a range of activities such as:
The bi0s Pentest team, an ethical hacking team, focuses on penetration testing and CTFs to detect and exploit vulnerabilities in networks, cloud appliances, and web-based systems. Team members actively participate in bug bounty programs, gaining hands-on experience in real-time bug-hunting.
An example for success of this practice is the participation of Team bi0s at Hacklu19, a prominent cyber security conference in Luxembourg. Students – Geethna T. K., Sruti Dixit, and Soumya, from the Department of Computer Science and Engineering, were awarded scholarships to attend the event and conduct workshops on “Intro to Dark Arts: Getting Started with CTFs.” These workshops introduced participants to Capture-The-Flag contests and real- world security skills, focusing on domains such as Cryptography, Reverse Engineering, and Binary Exploitation.
Training for Competitive Programming
Additionally, Competitive Programming is strongly encouraged through the ACM Student Chapter, established in 2016. The chapter, with over 100 members, offers networking opportunities and serves as a platform for students to enhance their technical and computing skills by connecting with peers, faculty, and industry professionals. The ACM chapter drives growth through five Student Interest Groups (SIGs) focused on:
These outside-classroom practices foster self-learning, collaborative teamwork, and real-world problem-solving skills, ensuring students are well- equipped for the evolving demands of the tech industry.
In-House Internship and Research-Oriented Projects
Department offers in-house internship opportunities aimed at fostering professional development and technical expertise among the students. These internships not only provide hands-on experience but also enhance students academic profiles by enabling them to contribute to the broader academic and professional communities. As part of this clubs initiatives, the students are getting opportunities to participate in cutting-edge research and projects leading to publications in national and international conferences. Each research project is supervised by a faculty mentor, who offers guidance and expertise throughout the process, ensuring high-quality research and successful paper publications. This collaboration between students and faculty strengthens the research output and reinforces our commitment to promoting research-oriented learning and professional growth in the computing discipline. The details of paper publication as part of ACM internship are provided in table below:
Mock Interviews & Industry Interactions
An innovative practice we employ is conducting Mock Interviews for S7 students, facilitated by a diverse panel of interviewers, including faculty, external experts, alumni, and industry professionals. This approach provides students with a comprehensive and real-world interview experience, helping them prepare for campus placements and professional careers. The involvement of alumni and industry experts adds valuable insights from current industry standards and expectations, while faculty and external experts contribute their academic perspectives, ensuring students receive well-rounded feedback and guidance.
Industry interaction for students is a crucial component of bridging the gap between academic learning and practical, real-world experience. We have provided opportunities for students to interact with industry resource persons from diverse companies, which offers unique insights into industry trends, emerging technologies, and the skills required to excel in professional environments. Such interactions enable students to understand and explore career opportunities while engaging in meaningful networking.
Talks by International Speakers
We provided students with the valuable opportunity to attend talks by international speakers, giving them exposure to diverse global perspectives and expertise. These sessions offered insights into cutting-edge research, emerging trends, and real-world applications from various fields, enabling students to broaden their knowledge beyond the classroom. By engaging with distinguished professionals and thought leaders from around the world, students were able to enhance their understanding of the global landscape, foster academic curiosity, and gain inspiration for their own academic and career pursuits.