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| Duration | Intake | Department | Approvals |
|---|---|---|---|
| 4 Years (8 Semesters) | 180 | AWS Oracle Academy Intel Intelligent Systems ARM | AICTE |
NIET offers a four-year under-graduate B.Tech course in Artificial Intelligence and Machine Learning which aims to develop a strong foundation by using the principles and technologies that consist of many facets of Artificial Intelligence including logic, knowledge representation, probabilistic models, and machine learning. This course is best suited for students seeking to build world-class expertise in Artificial Intelligence and Machine Learning and emerging technologies which help to stand in the crowd and grow careers in the upcoming technological era.
The course is designed to give the students enough exposure to the variety of applications that can be built using techniques covered under this program. They shall be able to apply AI/ML methods, techniques and tools to the applications. The students shall explore the practical components of developing AI apps and platforms. A proficiency in mathematics will prove to be beneficial as this degree requires strong problem-solving and analytical skills. They shall be able to acquire the ability to design intelligent solutions for various business problems in a variety of domains and business applications. The students shall be exploring fields such as neural networks, natural language processing, robotics, deep learning, computer vision, reasoning and problem-solving. The key objective is to identify logic and reasoning methods from a computational perspective, learn about agent, search, probabilistic models, perception and cognition, and machine learning.
Highlights- One of the college and the first ones to offer best in class B.Tech Program in Artificial Intelligence and Machine Learning
- Builds a solid foundation in advanced technologies of machine learning through industry-oriented curriculum
- Hands-on industry projects and regular sessions by industry experts
- Gain expertise in advanced topics such as robotics, machine learning, deep learning, pattern recognition, computer vision, cognitive computing, human-computer interaction etc.
To develop globally competent and ethical professionals, in the field of Artificial Intelligence and Machine Learning, ready to serve industry and society at large.
- To impart cutting-edge technology skills and competencies in the field of Artificial Intelligence and Machine Learning, thus producing industry-ready professionals and entrepreneurs.
- To collaborate with the leading industries to exhilarate innovative research and development in Artificial Intelligence and Machine Learning and its allied technologies.
- To inculcate ethical values amongst students who are always eager to address global issues for life-long learning.
Our graduates will be able to
- Pursue higher education and professional career to excel in the field of Artificial Intelligence and Machine Learning.
- Lead by example in innovative research and entrepreneurial zeal for 21st century skills.
- Proactively provide innovative solutions for societal problems to promote life-long learning.
Our graduates will be able to
- Design innovative intelligent systems for the welfare of the people using machine learning and its applications.
- Demonstrate ethical, professional and team-oriented skills while providing innovative solutions in Artificial Intelligence and Machine Learning for life-long learning.
Head, Department of AIML
Welcome to the Department of Artificial Intelligence & Machine Learning (AIML).
Department of Artificial Intelligence & Machine Learning (AIML) was established in 2020. The department seeks to combine excellence in education with service to the industry.
The Department of Artificial Intelligence & Machine Learning (AIML) aims to produce skilled professionals in the domain of Artificial Intelligence & Machine Learning and enable them to excel professionally. It also provides state-of-the-art laboratory facilities to the students to get better practical exposure and strong ties with industry, research organizations and the community.
This course enables students to build intelligent machines, software, or applications with a crisp combination of Machine Learning, Deep Learning, Analytics and Visualization technologies. The department aims to impart cutting-edge technology skills and competencies in various fields of Artificial Intelligence and Machine Learning, thereby producing industry-ready professionals and Entrepreneurs. The department will collaborate with the leading industries to exhilarate innovative research and development in Artificial Intelligence and Machine Learning and its allied technologies. The department covers a whole spectrum of research in Artificial Intelligence, Image Processing, Pattern Recognition, Machine Learning, Data Mining, Big-Data Analytics, Algorithms, and Computer Security led by a qualified and experienced team of faculty members.
Artificial Intelligence & Machine Learning has seen tremendous growth in the recent decade. It is an offshoot branch of Computer Engineering that has created a paradigm shift in almost every sector of the industry, academics and research. We are passionate to connect with industry sources and working alongside them to outsize the impact on the students with in-demand tools and technologies.
The students, faculty, and staff of AIML at NIET believe in working together, encouraging each other, helping each other and most importantly, belief & trust in each other. This is the key to making our students successful at NIET!
I am confident that the Department of Artificial Intelligence & Machine Learning at NIET is ready in all respect to face the new & exciting challenges in this new digital era and to be one of the best institutions in the state of Uttar Pradesh and India.
| Title | Click to Download |
|---|---|
| List of Faculty in AIML Department as on 22/07/2022 |  |
- Alisha Sikri, Bhawna Wadhwa, Anamika Tiwari, Dr. Vikas Sagar, Roshan Jameel, Sofia K. Pillai and Alka Singh, “System and method for HealthCare planning over multi-dimensional data”. Application No: 202211015022. Date of Publishing: 01/04/2022
- Alka Singh, “IoT Based Organic Compost Machine”. Application No: 345652-001. Date of Publishing: 03/07/2021
- Neelam, Rifa Khan Nizam, Rohit Choudhary, Priya Singh, Amita Shukla, Aradhna Saini, Gaurav Dhuriya, Ayushi Pandey “ A Gait Training System and method for using the same for Training A Patent” Application number :202211035750. Date of Publishing :22/06/2022
- Alka Singh, Poonam Ponde, “Home Automation: IoT”, International Conference on Intelligent Emerging Methods of Artificial Intelligence and Cloud Computing, pp 244-254, Vol. 273, DOI: 10.1007/978-3-030-92905-3_32.
- S A Rawandale, V N Kalbande, A Bodhe, U Rawandale, Ratna Patil , “Estimating the Employment Opportunity of Engineering Students with the Aid of Fuzzy Logic Controller” International Journal of Engineering Trends and Technology Volume 70 Issue 3, 319-326, March 2022 doi: https://doi.org/10.14445/22315381/IJETT-V70I3P236 ISSN: 2231 – 5381 © 2022 Seventh Sense Research Group
- Ratna Patil, Sharvari Tamane, Shitalkumar Adhar Rawandale, Kanishk Patil, “A modified mayfly-SVM approach for early detection of type 2 diabetes mellitus” International Journal of Electrical and Computer Engineering (IJECE) Vol. 12, No. 1, February 2022, pp. 524-533. http://doi.org/10.11591/ijece.v12i1.pp524-533 p-ISSN 2088-8708, e-ISSN 2722-2578
- Perti, A., Singh, A., Sinha, A., Srivastava, P.K. (2021). Title: Security Risks and Challenges in IoT-Based Applications. In: Tiwari, S., Suryani, E., Ng, A.K., Mishra, K.K., Singh, N. (eds) Title: Proceedings of International Conference on Big Data, Machine Learning and their Applications. Lecture Notes in Networks and Systems, vol 150. Springer, Singapore.https://doi.org/10.1007/978-981-15-8377-3_9.
- Ratna Patil, Ananya Tripathi, Yashasewi Singh and Gaurav Prajapati, “Facial Emotion Recognition Using Deep Learning: A case study” ICISSI 2022: International Conference on Intelligent Systems and Smart Infrastructure- Brijesh Mishra et al. Taylor & Francis Group, London, ISBN 978-1-032-41287-0
- Ratna Patil, Sharvari Tamane, Kanishk Patil, “An Experimental Approach Towards Type 2 Diabetes Diagnosis Using Cultural Algorithm” ICT Systems and Sustainability. Advances in Intelligent Systems and Computing, vol 1270. pp 405-415. AISC, volume 1270. Springer, Singapore. 15 December 2020. https://doi.org/10.1007/978-981-15-8289-9_39 ISSN: 2194-5357
- Ratna Patil, Sharvari Tamane, Nirmal Rawnadale, “Hybrid ANFIS-GA and ANFIS-PSO based models for Prediction of Type 2 Diabetes Mellitus” Computational Methods and Data Engineering. Advances in Intelligent Systems and Computing, AISC, volume 1227. pp 11-23. Springer, Singapore. 20 August 2020. https://doi.org/10.1007/978-981-15-6876-3_2 ISSN:2194-5357
- Ratna Patil, Sharvari Tamane, Kanishk Patil, “Self Organising Fuzzy Logic Classifier for Predicting Type-2 Diabetes Mellitus using ACO-ANN” International Journal of Advanced Computer Science and Applications. Vol. 11, No. 7, 2020. pp348-353. https://dx.doi.org/10.14569/IJACSA.2020.0110746 ISSN: 2156-5570
- Ratna Patil, Sharvari Tamane, “PSO-ANN-Based Computer-Aided Diagnosis and Classification of Diabetes” Smart Trends in Computing and Communications. Smart Innovation, Systems and Technologies, vol 165. pp 11-20. Springer, Singapore. 04 December 2019. https://doi.org/10.1007/978-981-15-0077-0_2 ISSN:2190-3018