Computer Science Engineering (AI & ML)

The Computer Science Engineering (AI&ML) program at R.R. Group of Institutions (RRGI) delves deep into the exciting world of artificial intelligence and machine learning, fields that are transforming industries globally. Covering a variety of topics, this program focuses on the development of intelligent systems through the analysis of algorithms, programming languages, data structures, deep learning, neural networks, and the integration of machine learning into real-world applications.

At RRGI, we pride ourselves on providing students with world-class infrastructure, including fully equipped labs, cutting-edge tools, and regular workshops that focus on the latest advancements in AI & ML. Our curriculum also includes industrial tours and hands-on projects, ensuring that students gain practical exposure and a competitive edge in the rapidly evolving tech landscape.

AI & ML have their roots in mathematics, computer science, and data science. While these fields were initially explored within specialized departments, they have now evolved into distinct branches of engineering. From the inception of the BTech program in Computer Science with a focus on AI & ML at RRGI, we have continuously adapted to emerging technologies, ensuring our students are at the forefront of innovation.

Our graduates from the CSE (AI&ML) department have demonstrated exceptional skills and have secured placements in top-tier IT and tech companies such as Wipro, Accenture, Capgemini, Zensar, and others, often with impressive salary packages. This achievement reflects our commitment to fostering professional excellence and producing industry-ready engineers who excel in the fields of Artificial Intelligence and Machine Learning.

Vision

To establish a scientific & technical environment which imparts quality education to achieve excellence in the field of Computer Science & Engineering specialised in Artificial Intelligence and Machine Learning to cater the evolving needs of the industry and society by maintaining human values, morals and ethics.

Mission

• M1-To provide quality education in the field of Computer Science & Engineering and latest concepts and techniques like Artificial Intelligence and Machine Learning by adopting high-quality academic practices which enable our students to meet the demands of academia, industry, nation and the world at large.
• M2-To motivate students for higher studies, employability and research activities for the betterment of society.
• M3-To induce students with professional behaviour, leadership, ethics, morality and Indian values.

• PEO1:- Graduate of the program will be able to apply theoretical and technical principles of Computer Science & especially latest technologies like Artificial Intelligence and Machine to analyze and provide innovative solutions to real-life problems.
• PEO2:- Graduate of the program will be technically and professionally competent for employability, research & development, higher education and entrepreneurship with a zeal for continuous learning in the field of Computer Science& Engineering and related domains.  
• PEO3:- Graduate of the program will be able to work individually as well as in teams with sound communicational skills.

• The graduates should have the excellent capability to solve the problems and do innovation in the area of algorithm, data sciences, network & securities, deep learning, and web application with the help of available tools, technologies, and resources.
• The graduates should have the ability to apply multidisciplinary approaches to formulate and develop products based on existing knowledge and research for the industry and societal real problems.

Name of the faculty	Designation	Qualification	Department
NEERAJ KUMAR	Assistant Professor & HOD	M. Tech	COMPUTER SCIENCE AND ENGINEERING (ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING )
SHIVA PANDEY	Assistant Professor	M. Tech	COMPUTER SCIENCE AND ENGINEERING (ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING )
ANCHAL SRIVASTAVA	Assistant Professor	M. Tech	COMPUTER SCIENCE AND ENGINEERING (ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING )
UMESH KUMAR	Assistant Professor	M. Tech	COMPUTER SCIENCE AND ENGINEERING (ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING )
SATYA NARAYAN YADAV	Assistant Professor	M. Tech	COMPUTER SCIENCE AND ENGINEERING (ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING )
SRISHTI GARG	Assistant Professor	M. Tech	COMPUTER SCIENCE AND ENGINEERING (ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING )
AKANKSHA YADAV	Assistant Professor	M. Tech	COMPUTER SCIENCE AND ENGINEERING (ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING )

• In the early days of their academic quest, students tread through realms of Mathematics, Physics, and Programming, forging the foundations of logic and computation.
• They journey next into the world of Data Structures and Object-Oriented Design, where structure meets creativity, and code becomes craft.
• The gates to deeper knowledge open with Operating Systems and Computer Architecture, revealing the invisible engines of modern machines.
• Database Management whispers the secrets of data, while Design & Analysis of Algorithms teaches the elegance of solving the unsolvable.
• Guided by the torch of Artificial Intelligence, learners meet agents that think, reason, and learn from the world.
• Soon after, Machine Learning joins the tale—algorithms that evolve, adapt, and predict, shaping the minds of tomorrow.
• Deep Learning emerges, weaving magic through neural networks, unlocking vision and language through computation.
• The voices of machines begin to form in Natural Language Processing, where syntax, semantics, and sentiment collide.
• Eyes open in Image Processing, as machines begin to see, analyze, and understand the world in pixels.
• Data becomes a storyteller in Analytics, painting truths with patterns and numbers.
• Electives beckon like side quests—IoT, Blockchain, Quantum Computing, and more await the curious.
• Open electives offer a broader vision: from smart cities to ethics, from entrepreneurship to robotics.
• Throughout, projects bring thought to life—mini-creations in third year, masterpieces in the final act.
• The narrative intertwines with real-world trials—internships and industry connections that bridge dreams and practice.
• And in quiet moments, lessons in ethics, society, and culture remind the engineer of their greater role in shaping the world.

The department has established the following laboratories:

• Artificial Intelligence Lab
• Machine Learning Lab
• Data Science / Data Mining Lab
• Database Management Systems Lab
• Python Programming Lab
• Data Structures & Algorithms Lab
• Computer Networks & Web Tech Lab
• Operating Systems Lab
• Cryptography & Network Security Lab
• Software Engineering Lab
• Distributed Systems Lab
• Image Processing / Graphics Lab

• In the heart of digital classrooms, where code becomes craft, students no longer just learn—they create.
• Lectures are flipped like pages in time, with wisdom whispered through videos watched beneath the stars.
• Gone are chalkboards of silence; now, screens light up with live coding, debates, and debugging battles.
• Professors guide not as sages, but as mentors—nudging minds into project-based quests through real-world puzzles.
• Neural networks and algorithms breathe life in labs where machines learn and students follow in awe.
• Each mini-project is a spark, each capstone a flame—ideas evolve into inventions.
• Hackathons roar like festivals, where sleep is optional but passion isn’t, and AI is forged in fire.
• Students and peers co-learn, collaborate on GitHub, review pull requests, and present code like poetry.
• A canvas of interdisciplinary colors paints AI with strokes of healthcare, art, and sustainability.
• Beyond numbers, they explore the soul of machines—bias, fairness, and the moral dance of decision-making.
• Virtual labs open portals where experiments need no wires, just wonder and Wi-Fi.
• NPTEL and MOOCs become midnight companions, as knowledge streams endlessly across borders.
• Internships blend learning with industry, where students touch the pulse of real data and deeper purpose.
• In every presentation, every published paper, echoes the journey of learning through doing.
• Thus, CSE (AI & ML) education becomes not a curriculum, but a story of curiosity, creation, and change.

Live demonstration can be an effective tool to present material in classroom and encourage student learning. Multimedia combines basic types of media into learning environment such as text, audio, video and graphics thus providing a powerful tool for teaching. This allows the students to pay more attention towards the concepts. It also helps the students to think and analyze the concepts in a better way.

Each One, Teach One Learning:

• In the quiet corners of the classroom, a spark is born—not in solitude, but in sharing.
• A lesson grasped becomes a story told, passed from mind to mind like a flame in the dark.
• One student, once a seeker, now stands tall—not as a master, but as a guide.
• For in this world of knowledge, the richest are those who give it away.
• Each question answered births a dozen more, and in their pursuit, two learners grow.
• No stage, no spotlight—just one friend helping another decode the world, one line at a time.
• Be it a loop in code, a flaw in logic, or a path in life—they learn together.
• The rhythm is simple: if I know it, I’ll teach it; if I don’t, I’ll ask—and soon, I will.
• This is not just teaching. It is trust.
• It is believing that every learner holds a teacher within.
• It is the symphony of voices in a lab, the scribbles on a whiteboard, the aha in a whisper.
• Here, every learner becomes a lantern—small, perhaps, but burning bright for someone else.
• And so, the classroom becomes a circle, not a hierarchy.
• Knowledge travels hand to hand, not top-down, but outward—like a ripple across time.
• And in the heart of this ripple, a truth echoes softly: to lift another is to rise yourself.

Virtual Labs Learning:

• In a world where walls no longer bind knowledge, the laboratory has evolved—from brick and mortar to bytes and bandwidth.
• No longer must a student wait their turn at a machine or be limited by tools too few or time too short.
• Now, with a click and a curious mind, the lab opens—not at school, but at home, in libraries, on buses, in midnight silence.
• Here, Virtual Labs become playgrounds of possibility.
• A place where circuits are drawn not by wires, but by will;
• Where algorithms come alive, and code speaks in colorful simulation.
• Where errors don’t cost equipment—but invite exploration.
• Every experiment is a second chance—run again, adjust again, learn again.
• Students from distant towns, lacking physical labs, now stand shoulder to shoulder with the world.
• No lab coat required—only curiosity, a browser, and belief.
• Teachers become mentors from afar; guidance flows through platforms like NIT Virtual Labs, AICTE’s tools, or open simulators.
• In this digital dimension, learning becomes limitless, scalable, and deeply personal.
• Mistakes are not feared but welcomed—because here, failure is just another version of success waiting to happen.

And so, Virtual Labs don’t just simulate machines—they ignite minds, empower learners, and dissolve barriers.

S. No.	Name of Laboratory	Webpage Link
1.	Artificial Intelligence Lab	https://ai1-iiith.vlabs.ac.in/
2.	Machine Learning Lab	https://cse22-iiith.vlabs.ac.in/
3.	Database Management Systems Lab	https://dsl.cds.iisc.ac.in/
4.	Data Structures & Algorithms Lab	https://xn--ds1iiith-2m3d.vlabs.ac.in/
5.	Computer Networks & Web Tech Lab	https://www.vlab.co.in/
6.	Operating Systems Lab	https://www.vlab.co.in/
7.	Software Engineering Lab	https://se-iitkgp.vlabs.ac.in/
8.	Distributed Systems Lab	https://dream-lab.in/
9.	Cryptography & Network Security Lab	https://cse29-iiith.vlabs.ac.in/
10.	Python Programming Lab	https://cse02-iiith.vlabs.ac.in/

The virtual lab stimulates students to conduct experiments by their curiosity. This would help them in learning basic and advanced concepts through remote experimentation. 

E-Learning:

E-Learning has become the silent revolution — where algorithms are explored in pajamas, and machine learning is mastered by moonlight.

From the quiet corners of homes, students now log into global classrooms —where NPTEL speaks with the voice of IITs, Coursera opens portals to Stanford and DeepLearning.ai, and YouTube becomes a blackboard of the world.

No longer bound by geography or time, CSE (AI & ML) students learn to build neural networks, train machines to see, speak, and decide — through recorded lectures, real-time code notebooks, and collaborative platforms like Kaggle, GitHub, and Google Colab.

E-learning empowers choice: to pause, to repeat, to explore deeper.It nurtures the independent thinker, the self-driven explorer, the coder who teaches themselves to teach machines.

Employability Skill Learning:

In view of the employability of the students, department has been providing the technical and soft skills classes throughout the session for overall grooming of the students. These classes empower students with confidence, serenity, fluency etc. Also, the overall students’ qualities are enhanced. These classes comprise of aptitude class and personality development class for two to three lectures per weeks for second, third and final year students. These classes are conducted by eminent faculties from training and placement department. During the class, regular assessment is done to observe the potential of the students. Based on the feedback, special emphasis is made to train the students to meet the requirements of the industry. These classes are highly valuable for the students who would be taking part in group discussions and interviews and campus drives.

Project-Based Learning:

Students work on projects that engage them in solving a real-world problem or answering a complex question, over an extended time and gain knowledge & skills by working for an extended time to investigate and respond to an authentic, engaging, and complex question, problem, or challenge.

They demonstrate their knowledge and skills by developing a product or presentation. As a result, students develop deep content knowledge as well as critical thinking, creativity, and communication skills in the context of doing an authentic, meaningful project. Project Based Learning unleashes contagious, creative energy among students and teachers. Sessions are arranged for demonstration of the working model of the projects, which is of utmost necessity for the students to have knowledge in hardware aspects.

Innovation in Laboratory Experiments:

To develop experimental skills, experience phenomena directly & Connect book knowledge to real-world applications in the students, all labs are equipped with latest equipments with standard operating procedures.

Simulations are also performed with the help of MATLAB/Simulink & other software tools for the program specific experiments.     

Workshop:

• The Department organized a hands-on Workshop on Python Programming to introduce students to modern programming practices.
• The workshop covered core Python concepts including variables, loops, functions, and data structures.
• Students were guided through real-time coding exercises using online platforms like Replit and Jupyter Notebook.
• Focus was placed on logical thinking, problem-solving, and writing clean, modular code.
• Advanced topics like file handling, exception handling, and basic object-oriented programming were also introduced.
• Participants developed mini-projects such as calculators, to-do apps, and data parsers.
• The sessions were interactive, with live coding demonstrations and one-on-one mentoring.
• Quizzes and coding challenges were conducted to reinforce learning outcomes.
• The workshop aimed to build a strong foundation in Python for further applications in AI, Data Science, and Web Development.
• All participants received certificates and access to workshop materials for continued learning.

Workshop on Various Software language

Question Bank Management System:

The management of question banks in the field of computer science and engineering (ai&ml)  is crucial for enhancing the efficiency of both teaching and learning processes. In the department, the management of question banks has been a manual task, with teachers responsible for typing and editing questions. Question bank structure is helpful for the various internal and external examinations as well as various competitive examinations. It includes almost all courses/ topics and difficulty level associated. A question bank for each course is prepared by concerned course instructor.

Innovative Assignment Practices:

In general practice, assignments are given to the students to improve knowledge through self-learning by referring available resources. But incorporating innovative methodology in the preparation of assignments the outcome is improved. One assignment per course outcome during the semester is assigned to improve learning ability and subject knowledge.

Mentor-Mentee Systems:

A small group of students are allocated to each faculty (mentor-mentee system). Faculty counsellor / Mentor prepare their students in individually for viva-voce & monitor their academic performance continuously.  Faculty counselor / Mentor monitor all the activities of the students.

Instructional Charts based Learning:

Many students are visual learners and understand concepts better when they are presented visually. The instructional charts are educational tools used by teachers to visually display information, an innovative tool in the teaching and learning process. 

Instructional Charts

These charts present data, illustrate concepts, outline processes, or provide guidelines in a visually engaging manner. The common benefits for the students are visual learning, engagement and interest, memory aid, encourages critical thinking, an alternative way to access and understand information.

Power point presentation based Learning:

Using, power point presentation, an innovative tool, the faculty can create & engaging visual presentations, allowing faculty and students to communicate ideas, information, and concepts effectively through slides that can include text, images, videos, and animation, etc. 

Video Lectures based Learning:

The department extensively practice video lectures based learning in using video as the primary medium for delivering educational content, offering a multisensory learning experience that combines audio, visuals, and text. The benefits for students are that videos can capture and maintain attention better than traditional text-based materials, leading to increased engagement and better knowledge retention, improved comprehension, and accessibility and convenience.

Seminars:  The faculty also utilizes the seminar-based teaching, a form of innovative learning, for students discussing pre-assigned questions or issues in small groups, guided by the teacher. 

Seminar Based Teaching

It encourages active participation, collaboration, and critical thinking, moving beyond traditional lecture-based learning. 

Expert Lectures:

In order to offer our students latest insights into the emerging technologies and advancements, expert lecture series are organized to help our students gain strong foothold in the field of computer science and engineering (ai&ml)  and help them stand out among the rest.

Instead of solely relying on traditional lectures, instructors can utilize expert lectures to provide foundational knowledge and then engage students in activities like research, application, and problem-solving. This approach fosters deeper understanding and encourages active learning. 

Guest Lectures/ Workshop /Industrial Visit	Date	Resource Person with designation / Organization
Guest lecture Scope of Artificial Intelligence: An Approach	16/03/2024	Dr. Upendra Kumar Deputy Dean of Student welfare Institute of Engineering And Technology  Lucknow, Uttar Pradesh
Workshop on Innovative Design using python and physical computing using Respberry-Pi	16/02/2024	Mr. Rohit Kumar Senior Trainer  Soft-Pro Training Academy  Lucknow
Workshop on Python	08/04/2024	Mr. Rohit Kumar Senior Trainer  Soft-Pro Training Academy  Lucknow

Name of Faculty	List of Publications with Title
Mr. Chandan Kumar	Machine learning algorithm based intelligent health care system for fast and accurate service/Patent /filling application date29/10/2022/the patent office journal No. 44/2022 dated 4/11/2022
	Phishing Email Detection Using Region Based Convolution Neural Network Model/ICTACSE-2022
	Vedic maths sutras and machine operations of a computer- a relationship/International Conference on Advanced Computing and Informatics (ICACI-2022)
	Phishing Email Detection Using Region Based Convolution Neural Network Model /Research (IJARST) /02 Feb-2022