A Three Days Techcamp on “Google AI-ML” was successfully organized by the Department of Computer Science and Engineering, Paavai Engineering College, in association with EduSkills Academy COE and Paavai Innovation Forum, from 19th February 2026 to 21st February 2026. The primary objective of the workshop was to provide students with practical exposure to Artificial Intelligence (AI), Machine Learning (ML), and Computer Vision technologies using modern Google-based platforms.
The workshop was conducted for 100 students, who actively participated in both theoretical sessions and practical demonstrations. The program aimed to equip students with essential knowledge of AI technologies and to provide hands-on experience in building machine learning models using modern tools.
The event was organized under the valuable guidance of the advisory members Dr.M.Premkumar, Principal, Paavai Engineering College, and Prof. Kamala Krishnamurthy, Centre Head, Paavai Innovation Forum.
The workshop was convened by Dr. D. Banumathy, Professor and Head, Department of Computer Science and Engineering. The event was coordinated by N.Karthica, AP/CSE, and R.Niranjana, AP/CSE, who ensured the smooth organization and successful execution of the workshop sessions.
The technical sessions were delivered by Mr. Ajeet Varma, Eduskills who served as the guest speaker. He provided insightful lectures along with practical demonstrations on Artificial Intelligence, Machine Learning, and Deep Learning technologies using platforms such as Google Colab and TensorFlow.
Day 1 – 19th February 2026
The first day of the workshop focused on introducing the fundamental concepts of Artificial Intelligence and Neural Networks. The guest speaker explained the evolution of AI and its growing importance in modern technology. Students were introduced to various AI applications used in industries such as healthcare, automation, robotics, and data analytics.
The first module titled “The Hello World of Deep Learning with Neural Networks” introduced participants to the basic concepts of Machine Learning and Deep Learning. Students learned about neural network structures, their functioning, and how data is used to train intelligent models.
The second module, “Define and Compile the Neural Network,” focused on the architecture of neural networks including layers, activation functions, loss functions, and optimizers. The speaker also explained how machine learning models are defined, compiled, and prepared for training.
During the practical session, students worked with Google Colab to implement simple neural network programs. This hands-on training enabled students to understand the workflow involved in developing and training machine learning models.
SESSION STARTED WITH FUNDAMENTALS OF AI AND NUERAL NETWORK
Day 2 – 20th February 2026
The second day of the Techcamp focused on Computer Vision and Convolutional Neural Networks (CNNs). The sessions explained how machines analyze and interpret visual data through deep learning techniques.
The first module, “Beyond Hello World – A Computer Vision,” introduced the concept of computer vision and its real-world applications such as facial recognition, object detection, and image classification. Students also learned about image datasets and the preprocessing techniques required for training AI models.
The second module titled “What are Convolutions?” explained the concept of convolution operations and how they are used to extract features from images. The guest speaker described how convolutional layers detect patterns such as edges, shapes, and textures, which are essential for image recognition.
These sessions helped students understand how CNN models process images and how they are used in applications such as autonomous vehicles, medical image analysis, and surveillance systems.
SPEAKER SESSION IS ON TOPICS INCLUDING COMPUTER VISION AND CONVOLUTIONAL NEURAL NETWORKS (CNNS)
Day 3 – 21st February 2026
The final day of the Techcamp focused on advanced implementation of Convolutional Neural Networks and model training techniques. Students were introduced to designing and optimizing deep learning models for improved performance.
The module “Using Convolutions” explained the architecture of CNN models, including convolution layers, pooling layers, and feature extraction techniques. The speaker also discussed optimization methods used to enhance model accuracy.
Another important session titled “Training with a Larger Dataset (Cats vs Dogs Model)” provided participants with practical experience in training machine learning models using large datasets. Students learned about data preprocessing, training and validation techniques, and model evaluation methods.
During the hands-on session, students implemented an image classification project using TensorFlow in Google Colab, where they trained a model to distinguish between cats and dogs images. This practical exercise significantly enhanced their understanding of machine learning workflows and deep learning model training.
SPEAKER EXPLAINING TOPICS ON ADVANCED IMPLEMENTATION OF CONVOLUTIONAL NEURAL NETWORKS AND MODEL TRAINING TECHNIQUES
The Three-Day Workshop on “Google AI-ML” proved to be highly informative and beneficial for all participants. The sessions conducted by Mr. Ajeeth Varma provided students with a strong foundation in Artificial Intelligence, Machine Learning, and Computer Vision technologies.
Through a combination of theoretical explanations and hands-on practical sessions, students gained valuable experience in using modern AI tools such as Google Colab and TensorFlow. The workshop encouraged students to explore advanced technologies and apply AI concepts in solving real-world problems.
With the enthusiastic participation of 100 students and the continuous support of the advisory members, convener, and coordinators, the workshop concluded successfully. The event received positive feedback from participants and served as an important step toward enhancing students’ technical skills in emerging AI and Machine Learning technologies. Certificates are provided to all 100 participants by Eduskills.
