The Department of Electronics and Communication Engineering, in association with Ethnotech, organized a Five-Day Workshop on Deep Learning using TensorFlow from 8th September to 13th September 2025 for 7th-semester students. The resource persons from Ethnotech provided hands-on training that combined theoretical foundations with practical implementation. This intensive workshop introduced the core concepts of deep learning and guided participants in building, training, and deploying neural network models using TensorFlow and Keras. The sessions also included real-world applications such as computer vision and natural language processing (NLP), enabling students to connect concepts with industry-relevant use cases.

During the five-day workshop, students were introduced to the fundamentals of deep learning and TensorFlow, followed by practical sessions on building Artificial Neural Networks (ANN). They explored advanced architectures such as Convolutional Neural Networks (CNN) for image-related tasks and Recurrent Neural Networks (RNN) for handling sequential data and natural language processing applications. The workshop concluded with sessions on model optimization, saving, and deployment, equipping students with end-to-end knowledge of developing and implementing deep learning solutions.

The objective of the workshop was to help students understand the essential concepts of deep learning and develop skills to create neural network models using TensorFlow and Keras. It also aimed to prepare them to apply CNNs and RNNs to real-world datasets, optimize models, and deploy them effectively.

By the end of the workshop, students were able to design, train, and deploy neural network models on real-world datasets. They gained valuable hands-on experience with TensorFlow and Keras, enhancing their technical expertise and readiness for careers or research in artificial intelligence and machine learning.