| Date | 15th December, 2025 |
| Mode | Online |
| Resource Person | Mr. Ganesh Naik |
| Coordinator | Ms. Ekta Ukey & Team CSI PHCET |
| Department | Computer Engineering |
Event Objective:
The primary objective of the workshop was to introduce students to the fundamentals of Deep Learning and Neural Networks, enabling them to understand how intelligent systems are designed, trained, and optimized. The session aimed to provide conceptual clarity along with practical exposure to modern AI tools used in real-world applications.
Event Outcome:
The NeuroNexus workshop provided participants with a strong conceptual foundation in deep learning and neural networks. Students gained insights into neural network architecture, training processes, and optimization techniques. Exposure to modern AI tools such as Hugging Face helped participants understand how pre-trained models are used in real-world applications. The workshop sparked interest in artificial intelligence and encouraged students to pursue further learning, projects, and research in deep learning and AI-driven technologies.
Number of attendees: 30+
CSI-PHCET successfully organized NeuroNexus, an online workshop focused on Deep Learning and Neural Networks, catering to students interested in artificial intelligence and emerging technologies. The workshop was designed to be accessible to beginners while also offering valuable insights for participants seeking to expand their knowledge of modern AI frameworks.
The session was conducted by Mr. Ganesh Naik, who began by explaining the evolution of artificial intelligence and the role of neural networks in solving complex problems. He provided a clear overview of how deep learning models mimic human cognitive processes and are applied in areas such as image recognition, natural language processing, and predictive analytics.
Mr. Naik introduced participants to the core concepts of neural networks, including neurons, layers, activation functions, and training mechanisms. He explained how neural networks are designed and optimized using training data and how performance improves through iterative learning.
The workshop further covered designing and training neural networks, where the speaker discussed model architecture, loss functions, and optimization techniques. Practical examples helped participants understand how neural networks are implemented and fine-tuned for real-world scenarios.
An important segment of the session was the introduction to Hugging Face, where Mr. Naik highlighted its role as a powerful platform for accessing and deploying pre-trained deep learning models. Participants gained insights into how such tools simplify AI development and accelerate experimentation.
The session encouraged active participation, with students engaging in discussions and asking questions related to deep learning applications, career pathways in AI, and learning resources. The speaker addressed these queries with practical guidance, making the session both informative and engaging.
By the end of the workshop, participants developed a foundational understanding of deep learning concepts, neural network design, and the use of modern AI tools, enabling them to take their first steps toward building intelligent systems.
The NeuroNexus workshop was a successful initiative that effectively introduced students to the principles and practical aspects of deep learning and neural networks. The event enhanced participants’ awareness of AI technologies and inspired them to further explore this rapidly evolving field.
Through workshops like NeuroNexus, CSI-PHCET continues to promote advanced technical learning and industry-relevant skills among students. The success of this event reinforces the organization’s commitment to fostering innovation, curiosity, and technical excellence within the student community.
