2 Years
Post Graduate
Engineering
Full Time
Subjects: Deep Learning, Computer Vision, NLP, Reinforcement Learning, GANs, Ethical AI, Research Methods.
The M.Tech. in Neural Networks course syllabus covers topics such as deep learning, neural network architectures, computer vision, natural language processing, reinforcement learning, and practical applications. Students also explore advanced topics like generative adversarial networks (GANs), ethical AI, and research methodologies. The program includes hands-on projects and research opportunities to deepen understanding and practical skills in this evolving field.
1st Year OR 1st & 2nd Semester Syllabus of Master of Technology (M.Tech.) in Neural Networks
| S.no | Subjects |
| 1 | Algorithms and Algorithmic Complexity |
| 2 | Cryptography and Network Security |
| 3 | Advanced Database Management Systems |
| 4 | VLSI Design |
| 5 | Embedded Systems |
| 6 | Advanced Software Engineering |
| 7 | Natural Language Processing |
2nd Year OR 3rd & 4th Semester Syllabus of Master of Technology (M.Tech.) in Neural Networks
| S.No | Subjects |
| 1 | Project |
| 2 | General viva voce |
| 3 | Seminar |
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