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Duration of Program 4 Years (8 Semesters)
Seats: 60
Artificial Intelligence is the branch of Computer Science concerned with making computers behave like humans!
The B.Tech program in Artificial Intelligence and Data Science at J.N.N Institute of Engineering combines cutting-edge curriculum in AI, machine learning and data analysis with practical, hands-on training. Located near Chennai, this program leverages state-of-the-art facilities and a lush green campus to offer a conducive learning environment. Accredited by the AICTE and affiliated with Anna University, the program aims to develop skilled professionals who are ready to tackle the challenges of the evolving tech landscape. Key Features :- Strategic Location: Accessible from Chennai with frequent bus services.
- Modern Infrastructure: Equipped with the latest technology and laboratories.
- Expert Faculty: Experienced educators and industry experts.
- Industry Collaboration: Strong links with leading tech companies ensuring relevant industry exposure.
Vision:
To impart quality-education, inculcate professionalism and enhance the problem-solving skills of the students in the domain of Artificial Intelligence & Data Science by applying recent technological tools and incorporating collaborative principles with a focus to make them industry ready.
Mission:
– To enhance the knowledge of the students with most recent advancements and refresh their insights in the field of Artificial Intelligence and Data Science.
– To equip the students with strong fundamental concepts, analytical capability, programming and problem-solving skills.
– To make the students industry ready and to enhance their employability through training, internships and real-time projects.
– To guide the students to perform research on Artificial Intelligence and Data Science, with the aim to provide solutions to the problems of the industry.
SEMESTER | SUB.CODE | LABORATORY NAME |
I | GE8161 | Problem Solving and Python Programming Lab |
II | AD8261 | Data Structures Design Lab |
III | AD8311 | Data Science Laboratory |
III | CS8383 | Object Oriented Programming Laboratory |
IV | AD8411 | Database Design and Management Laboratory |
IV | AD8412 | Data Analytics Laboratory |
IV | AD8413 | Artificial Intelligence – I Laboratory |
V | AD8511 | Machine Learning Lab |
V | AD8512 | Mini Project on Data Sciences |
V | IT8511 | Web Technology Lab |
VI | AD8611 | Artificial Intelligence – II Lab |
VII | AD8711 | Deep Learning Lab |
VII | AD8712 | Mini Project on Analytics |
VIII | AD8811 | Project Work |
Computer Society of India | |
Institution of Engineers, India | |
Indian Society of Technical Education | |
ICT Academy |
SPECIALIZATION | SEMESTER | SUB.CODE | PROFESSIONAL ELECTIVES |
Data Science & Analytics | IV | AD8002 | HEALTH CARE ANALYTICS |
VI | AD8006 | ENGINEERING PREDICTIVE ANALYTICS | |
VIII | AD8010 | SPEECH PROCESSING AND ANALYTICS | |
VIII | AD8081 | COGNITIVE SCIENCE AND ANALYTICS | |
VIII | AD8012 | NONLINEAR OPTIMIZATION | |
IOT | VI | CS8081 | INTERNET OF THINGS |
CYBER SECURITY | VIII | AD8011 | CYBER SECURITY |
Cloud | VI | CS8791 | CLOUD COMPUTING |
Software Development | IV | AD8001 | SOFTWARE DEVELOPMENT PROCESS |
VI | CW8591 | SOFTWARE ARCHITECTURE | |
VI | CS8072 | AGILE METHODOLOGIES |
PROGRAM EDUCATIONAL OBJECTIVES (PEOs)
- To provide graduates with the proficiency to utilize the fundamental knowledge of basic sciences, mathematics, Artificial Intelligence, data science and statistics to build systems that require management and analysis of large volume of data.
- To enrich graduates with necessary technical skills to pursue pioneering research in the field of AI and Data Science and create disruptive and sustainable solutions for the welfare of ecosystems.
- To enable graduates to think logically, pursue lifelong learning and collaborate with an ethical attitude in a multidisciplinary team.
PROGRAM OUTCOMES (POs) ENGINEERING GRADUATES WILL BE ABLE TO:
- Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and Artificial Intelligence and Data Science basics to the solution of complex engineering problems.
- Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
- 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.
- 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.
- Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.
- The engineer and 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.
- 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.
- Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
- Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
- 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.
- 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 environment
- 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 changes.
PROGRAMME SPECIFIC OUTCOMES (PSO’s)
- Graduates should be able to evolve AI based efficient domain specific processes for effective decision making in several domains such as business and governance domains.
- Graduates should be able to arrive at actionable Fore sight, Insight , hind sight from data for solving business and engineering problems
- Graduates should be able to create, select and apply the theoretical knowledge of AI and Data Analytics along with practical industrial tools and techniques to manage and solve wicked societal problems.
Regulations 2022 – View/Download
Regulations 2021 – View/Download
Regulations 2017 – View/Download
The B.Tech in AI and Data Science covers a range of subjects from basic programming to advanced AI technologies. The curriculum is designed to balance theoretical knowledge with practical applications, ensuring students are job-ready upon graduation.
Core Subjects :
– Machine Learning
– Deep Learning
– Big Data Analytics
– Neural Networks
– AI Ethics
Elective :
– Robotics
– Natural Language Processing
– Reinforcement Learning
– Cloud Computing in AI
– Eligibility: Candidates must have completed their 10+2 education with Mathematics and Physics as core subjects.
– Fees: The fee structure is competitive and designed to be inclusive. For detailed information, prospective students should contact the admissions office.
This course was started in 2020-2021 AY and students are currently pursuing their 2nd year. Relevant content will be added soon.
This course was started in 2020-2021 AY and students are currently pursuing their 2nd year. Relevant content will be added soon.
Frequently Asked Questions (FAQ) about B.Tech Artificial Intelligence and Data Science
The program is structured to be completed over four years, divided into eight semesters.
Yes, the institute facilitates internships with top tech companies and startups through its industry partnerships to provide practical experience.
Graduates can pursue careers as AI specialists, data analysts, machine learning engineers and more in industries ranging from healthcare to finance and tech startups.
J.N.N offers comprehensive hostel facilities and transportation services to ensure a comfortable stay for all students.
Yes, students are encouraged to engage in research under the guidance of faculty members and through collaborations with industry partners. For further information about the B.Tech in Artificial Intelligence and Data Science at J.N.N Institute of Engineering or to apply, please visit the institution’s official website or contact the admissions office.