Introduction to Deep Learning

This 4-day hands-on training will introduce you to the foundations of deep learning, equipping you with the skills to build, train, and evaluate neural networks using industry-standard frameworks (TensorFlow, Keras, PyTorch). You will gain practical experience with real-world datasets, computer vision, and natural language processing projects.

🧠 What You’ll Learn

• Understand the principles of deep learning and neural networks

• Set up and use TensorFlow, Keras, and PyTorch frameworks

• Build and train feedforward and convolutional neural networks (CNNs)

• Explore techniques for model optimization (regularization, dropout, batch normalization)

• Work with image datasets for classification and object detection

• Apply recurrent neural networks (RNNs) for sequence data and text processing

• Implement transfer learning with pre-trained models (ResNet, BERT)

• Develop end-to-end mini-projects in computer vision and NLP

👥 Who Should Take This Training?

• Engineers and developers exploring AI and deep learning applications

• Data scientists and analysts ready to move from ML to deep learning solutions

• Researchers and professionals aiming to use neural networks in their field

• Anyone with a technical or scientific background, some Python knowledge recommended

🎯 What You’ll Achieve

• Build and evaluate neural networks for structured, image, and text data

• Apply best practices for training deep learning models efficiently

• Use transfer learning to accelerate AI project development

• Gain the ability to design and implement AI-powered solutions in real-world scenarios

• Strengthen your foundation to advance into specialized areas (computer vision, NLP, reinforcement learning)

✅ Prerequisites

• Basic knowledge of Python and machine learning concepts recommended

• University-level background in math (linear algebra, probability, calculus) helpful but not mandatory