Welcome to the Department of Artificial Intelligence and Data Science!
Department of Artificial Intelligence & Data Science was established in the year 2023 with an intake of 60 seats/year. .Here, we’re all about exploring the incredible potential of technology to solve real-world problems. Our team is a passionate mix of students, researchers, and faculty members, all working together to push the boundaries of AI and data science. Whether you're interested in machine learning, data analytics, or the many other fields within this ever-evolving space, we have something exciting for you. We believe in hands-on learning, innovation, and making an impact—our work isn’t just about coding or algorithms; it’s about creating solutions that can change industries and improve lives. We foster a collaborative and supportive environment, where creativity thrives, and we’re committed to developing the next generation of leaders in tech. Whether you're here to gain technical expertise, dive into groundbreaking research, or develop your career in one of the world’s fastest-growing fields, we’ve got the resources, knowledge, and inspiration to help you succeed. Let’s explore the future of technology, together!
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Welcome to the Department of Computer Science and Engineering (CSE-AI & Data Science), where innovation meets excellence. Our mission is to equip students with cutting-edge knowledge and hands-on experience, preparing them to become pioneers in the fields of Artificial Intelligence and Data Science.
Our Artificial Intelligence & Data Science program integrates AI-driven decision-making with analytical expertise, enabling students to extract meaningful insights from large datasets using advanced AI algorithms, data mining, and predictive modeling. This curriculum empowers students to design intelligent systems that drive innovation across industries, preparing them for impactful careers in AI research, data analytics, and AI applications.
The Artificial Intelligence program delves deep into the world of intelligent systems, covering machine learning, neural networks, natural language processing, and computer vision. Students acquire a robust foundation in AI technologies, developing industry-relevant solutions to solve real-world challenges.
Join us in redefining the future of technology through AI and Data Science.
We are dedicated to fostering technological innovation and academic excellence in Artificial Intelligence and Data Science. Our programs are designed to provide a balanced blend of theoretical knowledge and practical expertise, preparing students to become future leaders in AI-driven industries. Through rigorous research, creative exploration, and ethical AI practices, we empower students to tackle complex, real-world challenges and drive transformative change in society.
Our vision is to be a globally recognized center of excellence in AI and Data Science education. We emphasize collaboration, interdisciplinary research, and real-world applications, producing graduates who lead transformative advancements across industries such as healthcare, finance,robotics, cybersecurity, automation, and beyond. Our ultimate goal is to leverage AI and Data Science for sustainable innovation and societal impact.
PEO-1: Analytical Proficiency: Graduates will develop expertise in problem-solving, critical thinking, and decision-making, enabling them to address computational challenges in real-world applications.
PEO-2: Technical Excellence: Graduates will be equipped with cutting-edge technical skills, preparing them for immediate industry deployment, advanced certifications, higher education, and research
PEO-3: - Leadership & Communication: Graduates will excel in communication, teamwork, leadership, and career management, fostering professional growth and industry readiness
PEO-4: Ethical & Professional Responsibility Graduates will demonstrate a strong commitment to ethical standards, professional conduct, and technological adaptability in AI and Data Science.
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PO-1:Core Engineering Knowledge:Applying fundamental principles of mathematics, science, and engineering to solve complex AI-driven challenges.
PO-2:Advanced Problem-Solving:Identifying, analyzing, and formulating solutions for complex computational problems through research-driven methodologies
PO-3:Innovative System Design: Designing and implementing state-of-the-art AI solutions while ensuring safety, ethics, and societal impact.
PO-4:Industry-Relevant Research: Engaging in research methodologies, data analysis, and experimental investigations to provide innovative and practical AI solutions.
PO-5:Modern Technological Proficiency: Utilizing advanced tools, programming languages, and AI frameworks to develop scalable applications.
PO-6:Societal & Ethical AI Integration: Assessing the societal, environmental, and ethical implications of AI applications.
PO-7:Sustainability & Environmental Awareness Promoting AI-driven innovations for sustainable development and global impact.
PO-8:Professional Ethics & Responsibility: Upholding industry standards, ethical AI practices, and responsible innovation.
PO-9:Teamwork & Interdisciplinary Collaboration: Functioning effectively in team-driven and cross-functional environments.
PO-10: Effective Communication: Developing expertise in technical documentation, AI presentations, and stakeholder engagement.
PO-11:AI Project Management & Finance: Applying business and financial acumen in managing AI-driven projects.
PO-12: Lifelong Learning: Engaging in continuous learning to adapt to evolving AI technologies and industry advancements.
PSO-1: Attain a comprehensive understanding of computing systems and apply this knowledge to develop innovative AI and data-driven solutions.
PSO-2: Master programming languages, software development methodologies, and system analysis, enabling them to design, test, and deploy scalable AI solutions across industries.
| S.NO | Faculty Name | Highest Qualification | Experience | |
|---|---|---|---|---|
| 1. | Dr. Vandana Agarwal (Head) | Ph.D. (Mathematics), M.Tech., MCA | 23 Years | hod_ai_ds_127@iimtindia.net |
| 2. | Mr. Navnish Goel (Asst. Prof.) | M.Tech | 22 Years | navnishgoel_cse@iimtindia.net |
| 3. | Ms. Jolly Sharma (Asst. Prof.) | M.Tech | 5 Years | jollysharma_cse_127@iimtindia.net |
| 4. | Mr. Bhramreshwar Jha (Asst. Prof.) | MCA | 20 Years | bhramreshwarjha_cse@iimtindia.net |
| 5. | Ms. Sonia (Asst. Prof.) | M.Tech | 3 Years | soniya_cse@iimtindia.net |
| Programme | Duration | Eligibility |
|---|---|---|
| B.Tech CSE-AI & AI with Data Science | 4 Years |
Admission Criteria: |
After the course, students should be able to:
1. To develop simple algorithms for arithmetic and logical problems.
2. To translate the algorithms to programs & execution (in C language).
3. To implement conditional branching, iteration and recursion.
4. To decompose a problem into functions and synthesize a complete program using divide and conquer approach.
5. To use arrays, pointers and structures to develop algorithms and programs. Know the basic concepts of Function, Array and Link-list.
After the course, students should be able to:
1. Students will be enabled to understand the basic objective of the course by being acquainted with specific dimensions of communication skills i.e. Reading, Writing, Listening, Thinking and Speaking.
2. Students would be able to create substantial base by the formation of strong professional vocabulary for its application at different platforms and through numerous modes as Comprehension, reading, writing and speaking etc.
3. Students will apply it at their work place for writing purposes such as Presentation/official drafting/administrative communication and use it for document/project/report/research paper writing.
4. Students will be made to evaluate the correct & error-free writing by being well versed in rules of English grammar & cultivate relevant technical style of communication & presentation at their work place & also for academic uses.
5. Students will apply it for practical and oral presentation purposes by being honed up in presentation skills and voice-dynamics. They will apply techniques for developing interpersonal communication skills and positive attitude leading to their professional competence.
After the course, students should be able to:
1. Know the basic concepts of Function, Array and Link-list.
2. Analyze algorithms and algorithm correctness
3. Analyze space and time efficiency of searching and sorting techniques.
4. Describe stack, queue and linked list operation.
5. Implement tree and graphs concepts.
After the course, students should be able to:
1. Understand basic structure of computer.
2. Perform computer arithmetic operations.
3. Understand control unit operations.
4. Design memory organization that uses banks for different word size operations.
5. Understand the concept of cache mapping techniques.
6. Understand the concept of I/O organization
After the end course, students should be able to:
1. Develop static web pages using HTML.
2.Develop Java programs for window/web-based applications.
3. Design dynamic web pages using Javascript and XML.
After the course, students should be able to:
1. Understand and implement basic services and functionalities of the operating system Using system calls.
2. Analyze and simulate CPU Scheduling Algorithms like FCFS, Round Robin, SJF and Priority.
3. Implement memory management schemes and page replacement schemes.
4. Simulate file allocation and organization techniques.
5. Understand the concepts of deadlock in operating systems and implement them in multiprogramming system.
After the course, students should be able to:
1. A hands on workshop focusing on cyber security practices and technologies
After the course, students should be able to:
1. To understand usages of python and learning elementary steps of python
2. To understand use of iterative statements &Decision making statements. to understand string manipulation functions &listing concepts.
3. To understand use of Array and Functions for various purpose
4. To understand building structural records, searching concepts of data, organizing data, and recursive techniques.
5. To understand the concepts of class builing, instance creation and usintg methods of instances.
6. To learn drawing objects of different shapes, multiple object creation, handling their movements &designing them
7. To understand use of NumPy arrays, accessing data in NumPy, Fuctions of NumPy, Mathematical operations using NumPy
8. To understand and implement concepts of Data science and using their industrial applications
At the end of course, the student will be able to:
1. Understand and apply oracle 11 g products for creating tables, views, indexes, sequences and other database objects.
2. Design and implement a database schema for company data base, banking data base, library information system, payroll processing system, student information system.
3. Write and execute simple and complex queries using DDL, DML, DCL and TCL.
4. Write and execute PL/SQL blocks, procedure functions, packages and triggers, cursors.
5. Enforce entity integrity, referential integrity, key constraints, and domain constraints on database
At the end of course, the student will be able to:
1. Use of python to understand the concept of AI K3 .
2. Implementation of Different AI Techniques K4, K5 .
3. Application of AI techniques in practical Life K4 .
4. Understanding of Natural Language Tool Kit. K2
5. Practical Application of Natural Language Tool Kit K4, K5
At the end of course, the student will be able to:
1. Implement algorithm to solve problems by iterative approach.
2. Implement algorithm to solve problems by divide and conquer approach.
3. Implement algorithm to solve problems by Greedy algorithm approach.
4. Implement algorithm to solve problems by Dynamic programming, backtracking, branch and bound approach.
5. Implement algorithm to solve problems by branch and bound approach.
At the end of course, the student will be able to:
1. Discover potential research areas in the field of IT
2. Compare and contrast the several existing solutions for research challenge
3. Demonstrate an ability to work in teams and manage the conduct of the research study
4. Formulate and propose a plan for creating a solution for the research plan identified
5. To report and present the findings of the study conducted in the preferred domain
At the end of course, the student will be able to:
6. Identify ambiguities, inconsistencies and incompleteness from a requirements specification and state functional and non-functional requirement.
7. Identify different actors and use cases from a given problem statement and draw use case diagram to associate use cases with different types of relationship.
8. Draw a class diagram after identifying classes and association among them.
9. Graphically represent various UML diagrams, and associations among them and identify the logical sequence of activities undergoing in a system, and represent them pictorially.
10. Able to use modern engineering tools for specification, design, implementation and testing.
At the end of course, the student will be able to:
1. At the end of course, the student will be able to
2. Implement numerical and statistical analysis on various data sources K3
3. Apply data preprocessing and dimensionality reduction methods on raw data K3
4. Implement linear regression technique on numeric data for prediction K3
5. Execute clustering and association rule mining algorithms on different datasets K3
6. Implement and evaluate the performance of KNN algorithm on different datasets K3, K4
At the end of course, the student will be able to:
1. Simulate different network topologies.
2. Implement various framing methods of Data Link Layer.
3. Implement various Error and flow control techniques.
4. Implement network routing and addressing techniques.
5. Implement transport and security mechanisms.
At the end of course, the student will be able to:
1. Students will be able to understand the basics of distributed system ,event synchronization and termination detection.
2. Students will be able to learn the exclusive access to critical section ,successive factor of exclusion algorithms and basic concepts of deadlock.
3. Students will be able to apply the concept of distributed system to implement distributed shared memory and will learn about the agreement protocols.
4. Students will be able to apply the various algorithm for fault tolerant and recovery they will have basic idea of commit protocols.
5. Students will be able to build a fault tolerant Distributed system including the concept of concurrency control, transaction recovery and replication.
At the end of course, the student will be able to:
1. To provide the learning platform to students to enhance their employ ability skills along with real corporate exposure.
2. To enhance students’ knowledge in current technology.
3. To develop leadership ability and responsibility in student to execute the given task.
4. To Increase self-confidence of students and helps in finding their own proficiency.
5. To provide students hands on practice within a real job situation.
At the end of course, the student will be able to:
1. Formulate a real world problem and develop its requirements.
2. Develop a design solution for a set of requirements.
3. Test and validate the conformance of the developed prototype against the original requirements of the problem.
4. Work as a responsible member and possibly a leader of a team in developing software solutions .
5. Express technical and behavioural ideas and thought in oral settings.
6. Participate in and possibly moderate, discussions that lead to making decisions.
7. Express technical ideas, strategies and methodologies in written form.
8. Prepare and conduct oral presentations.
9. Self learn new tools, algorithms, and/or techniques that contribute to the software solution of the project.
10. Generate alternative solutions, compare them and select the optimum one.
At the end of course, the student will be able to understand
1. Developing a technical artifact requiring new technical skills and effectively utilizing a new software tool to complete a task
2. Writing requirements documentation, Selecting appropriate technologies, identifying and creating appropriate test cases for systems.
3. Demonstrating understanding of professional customs & practices and working with professional standards.
4. Improving problem solving, critical thinking skills and report writing.
5. Learning professional skills like exercising leadership, behaving professionally, behaving ethically, listening effectively, participating as a member of a team, developing appropriate workplace attitudes
At the end of course, the student will be able to:
1 Analyze and understand the real life problem and apply their knowledge to get programming solution.
2.Engage in the creative design process through the integration and application of diverse technical knowledge and expertise to meet customer needs and address social issues.
3. Use the various tools and techniques, coding practices for developing real life solution to the problem.
4. Find out the errors in software solutions and establishing the process to design maintainable software applications
5. Write the report about what they are doing in project and learning the team working skills
