A hands-on workshop designed to dive deep into neural networks and computer vision, two of the most powerful fields in Artificial Intelligence. This lab is practice-oriented and equips you with the knowledge and tools to build cutting-edge applications such as object detection, facial recognition, and autonomous systems.

🔹 What you’ll learn:

• Neural Networks Foundations: Understanding perceptrons, activation functions, backpropagation, and optimisation.

• Convolutional Neural Networks (CNNs): How they work and why they’re the backbone of computer vision.

• Image Processing: Techniques for preprocessing and augmenting datasets (resizing, normalisation, augmentation).

• Hands-On Projects: Build real models for image classification, object detection, and segmentation.

• Frameworks & Tools: Work with TensorFlow, Keras, and PyTorch to design and train deep learning models.

• Transfer Learning: Using pre-trained models (ResNet, VGG, YOLO) to accelerate development.

• Advanced Applications: From healthcare imaging to autonomous driving and surveillance systems.

🔹 Who it’s for:

• Learners who already have basic knowledge of Machine Learning and want to advance to Deep Learning.

• Developers and engineers aiming to specialise in Computer Vision.

• Professionals and researchers looking to apply DL to real-world challenges.

🔹 Why this course:
This lab goes beyond theory — it is project-driven and focuses on real-world implementations. You’ll leave with practical skills and working prototypes that demonstrate your ability to create powerful AI solutions in vision-based tasks.