B.Tech Artificial Intelligence and Data Science

About the Department

Department of Artificial Intelligence and Data Science started in the year 2020. The JIT Campus being a great place to learn & get nurtured, offers B.Tech. Programme in Artificial Intelligence & Data Science to cater the needs of tomorrow in all domains. Based on the infrastructure facility and faculty strength, the department was accorded approval by AICTE, New Delhi and affiliated to Anna University, Chennai to offer UG Programme.

The Department has excellent infrastructure in terms of laboratories, classrooms, seminar hall, Centre of Excellence, etc. The department laboratories are interconnected through a well-designed seamless network with Internet facility with the speed of 200 Mbps to facilitate the student’s access to web resources. This helps the students in meeting the demands of the regular curriculum and latest technology needs. With the co-operation and involvement of the dedicated team of well-qualified faculty members, the department constantly strives to improve its academic standards. Our students involve in developing the solutions for real time industrial problems and participate in national level and international level competitions and brought laurel to the department. Students learn in-demand skills in Artificial intelligence, Machine Learning, Deep Learning, Robotic Process Automation, NLP and Internet of Things to unlock the best roles in the near future.

Artificial Intelligence and Data Sciences (AI & DS) is one of the popular courses among engineering aspirants which mainly focuses on computation, analysis of algorithms, programming languages, program design, software engineering, computer hardware, computer networks and problem solving skills. This program has roots in electrical, electronics and communication engineering, mathematics, and linguistics. Students study the design, development and analysis of software and hardware used to solve problems for various business, scientific and social contexts. Since computers solve most of the complex problems in a simplified way, it provides the sophistication to the world and touches the human lives in all the aspects such as education, transportation, entertainment, banking, mass communication, social media, hospital management, businesses, supply chain management, etc. Artificial Intelligence and Data Sciences is inherently an interdisciplinary subject, it link to the disciplines including psychology, biology, mathematics, physics, education, art and music with the subjects of bioinformatics, electronics, operations research, theory of computation, help students to understand how Artificial Intelligence and Data Sciences fits in to a wide range of domains in the world.

Programme Scope

The biggest ever technological advancement this century has witnessed is making machines to think and act like human, engaging the science of Artificial Intelligence, powered by Data. AI driven by Data will be dominant in every aspect of human life with the scope for its application becoming limitless. Autonomous Vehicles, Virtual Assistants (Alexa, Siri), Domestic Assistants (maid robots), are some of the existing examples, while many are being developed every single day. The field of AI & DS is emerging as the most promising one for young engineers who have a flair for data and visualization.

This program prepares the students for career as Software Developers, Hardware Engineers, System Designer, System Analyst and Architect, Networking Engineers and Administrators, Database Administrator, web developers, Project Team Associate and Leaders etc. This program enable the students to acquire multidimensional approach of computing knowledge and understanding the problems to solve deep, imagination and sensitivity to a variety of concerns. The courses such as computer graphics, artificial intelligence, human computer interaction, robotics, database management, web technology, network security, grid and cloud computing and cyber security are applied to analyse and design the solutions to the real time complex problems such as development of computer models and software to improve education, 3D graphics to visualize historical artifacts, developing, understanding natural language, analysing medical images, using computers to produce art, and developing algorithms to support advanced network technologies.

Interpretation and prediction of business results and the future are no longer rocket science with a variety of techniques and tools such as statistical analysis, data aggregation, and data mining.

Students studying this programme will be able to design, develop and apply AI and DS based solutions to real world business challenges. The students will know to develop out insights with intellectual curiosity, by learning various technologies including Deep learning, Computer Vision, Data Science, Predictive Analytics, AR/VR, Natural Language Processing and Robotics, Software Technologies, OOPs and Database Management Systems.

Career Progression

With rapidly increasing focus on AI & DS by the industry, the students have abundant scope for employment in various industries including.

• Machine Learning Engineer.
• Data Scientist.
• Artificial Intelligence Engineer.
• Data Analyst.
• Machine Learning Architect.
• Healthcare.
• Travel & Transportation.
• Fast Moving Consumer Goods (FMCG).
• In Government for Engineering services, Remote sensing, E-Governance, etc.
• In PSU`s like EDP officers in Banking sectors, Railways, Airport Authorities of India, ONGC and Petroleum Corporations, etc.
• In Core Sectors like Tata Consultancy Services, Infosys, Virtusa, IBM, Cognizant Technologies, Zoho Coorporation, Vodafone, Rapid-I, Revature, etc.
• In Private Sectors as Business Development Associates, Content Development Manager, Financial Advisor and Consultant, etc.
• It also provide the opportunities and eligibility to write UPSC – IES (Indian Engineering Services).

Program Highlights

• Headed by a Senior Professor
• Experienced faculties on specialized subjects/topics
• Value Added Courses
• Choice based Credit System
• Industry Collaborated Value added Courses
• Internships
• Mentor – Mentee System
• Proctoring & Remedial system

Program Educational Objectives (PEO’s)

PEO1: Apply strong foundations in Mathematics, Statistics, Computing, and Artificial Intelligence to design and implement scalable data-driven intelligent systems.

PEO2: Excel as AI and Data Science professionals, researchers, or entrepreneurs by developing innovative and ethical solutions for complex societal and industrial problems.

PEO3: Engage in lifelong learning through higher education, research, certifications, and professional development in emerging AI technologies.

PEO4: Demonstrate leadership, teamwork, ethical responsibility, and social commitment in deploying responsible and sustainable AI systems.

Programme Outcomes (PO’S)

Engineering Graduates will be able to:

PO1: Engineering Knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.

PO2: Problem Analysis: Identify, formulate, review research literature, and analyse complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.

PO3: Design / Development of solutions: Design / Development of solutions: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.

PO4: Conduct Investigations of Complex problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.

PO5: Modern Tool Usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modelling to complex engineering activities with an understanding of the limitations.

PO6: The Engineer Society: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.

PO7: Environment and Sustainability: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.

PO8: Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.

PO9: Individual and Teamwork: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.

PO10: Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.

PO11: Project Management and Finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.

PO12: Life Long Learning: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.

Programme Specific Outcomes (PSOs)

PSO1: Analyze structured and unstructured data to generate actionable insights (foresight, insight, hindsight) for informed decision-making in business and engineering domains.

PSO2: Design and deploy intelligent systems using AI, Machine Learning, Deep Learning, Data Analytics, Cloud Platforms, and Big Data tools for applications in healthcare, agriculture, education, smart transportation, environment, and smart systems.

PSO3: Apply advanced AI algorithms, statistical models, and industrial tools to develop scalable, secure, ethical, and sustainable AI-enabled solutions for multidisciplinary and societal challenges.

Vision

To emerge as a Centre of Excellence in Artificial Intelligence and Data Science by fostering innovation, ethical intelligence, advanced research, and sustainable data-driven solutions for global and societal transformation.

Mission

• To deliver outcome-based education through contemporary curriculum, experiential learning, and industry-integrated pedagogy in Artificial Intelligence, Machine Learning, Data Science, Generative AI, and High-Performance Computing.
• To empower students with strong analytical, computational, and problem-solving skills to develop intelligent systems for real-world applications.
• To promote interdisciplinary research, innovation, and entrepreneurship through industry collaboration, incubation support, funded projects, and global partnerships.
• To create a student-centric learning ecosystem that encourages creativity, critical thinking, ethical AI practices, and lifelong learning.
• To develop sustainable AI-driven solutions addressing societal challenges in healthcare, agriculture, education, smart cities, environment, and governance.

Quality Objectives

• To achieve CO–PO attainment levels above the target benchmark (≥ 60%) with continuous academic improvement.
• To increase research output through publications in indexed journals, patents, funded research projects, and consultancy.
• To organize technical events such as hackathons, AI bootcamps, FDPs, conferences, and industry-certified training programs annually.
• To improve placement, higher education admissions, and AI-based start-up ventures year by year.
• To establish active MoUs with industries, research labs, and global academic institutions.
• To integrate emerging technologies such as Generative AI, Edge AI, Quantum AI, and Responsible AI into curriculum and projects.

Faculty

Syllabus

B.Tech., AIDS - 2025 Regulation

B.Tech., AIDS - 2021 Regulation

Lab

Data Science Laboratory

The Data Science Laboratory provides hands-on experience in data analysis, visualization, and machine learning. It enables students to work with real-world datasets using modern data science tools and techniques. The lab supports practical learning in statistics, programming, data mining, and artificial intelligence. It encourages innovation, research, and data-driven problem solving. The laboratory bridges theoretical concepts with real-time applications.

Machine Learning Laboratory

The Machine Learning Laboratory provides hands-on training in designing, implementing, and evaluating machine learning models. It helps students understand data preprocessing, algorithm selection, and model performance analysis. The laboratory enhances practical skills through real-world datasets and encourages problem-solving, innovation, and research-oriented learning.

• Helps students build, train, and evaluate ML models.
• Enhances skills in data preprocessing and model analysis.
• Supports real-world applications and problem solving.

Database and Design Management Laboratory

The Database and Design Management Laboratory equips students with practical expertise in designing, developing, and maintaining robust database systems. It emphasizes structured data modeling, query optimization, and database administration practices. The laboratory enables learners to apply theoretical concepts to real-time scenarios, ensuring reliable data storage, retrieval, and management in modern applications.

• The laboratory promotes best practices in database security, integrity, and performance tuning.
• It supports hands-on learning using industry-standard database management tools.

Deep Learning Laboratory

The Data Science Laboratory provides hands-on experience in data analysis, visualization, and machine learning. It enables students to work with real-world datasets using modern data science tools and techniques. The lab supports practical learning in statistics, programming, data mining, and artificial intelligence. It encourages innovation, research, and data-driven problem solving. The laboratory bridges theoretical concepts with real-time applications.

Placement

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Achievements

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Event

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