Deep Learning with Python

Month 1: Introduction to Deep Learning

• Introduction to Artificial Intelligence and Machine Learning
• What is Deep Learning?
• Neural Networks and their architecture
• Fundamentals of Linear Algebra, Probability and Statistics
• Popular frameworks and libraries for Deep Learning

Month 2: Fundamentals of Deep Learning

• Building blocks of Neural Networks: layers, activation functions
• Loss Functions and Optimization Algorithms
• Hyperparameter Tuning
• Convolutional Neural Networks (CNNs) for Image Classification
• Recurrent Neural Networks (RNNs) for Sequence Learning

Month 3: Advanced Deep Learning Techniques

• Transfer Learning
• Generative Adversarial Networks (GANs) for image generation
• Autoencoders for Image Compression and Denoising
• Reinforcement Learning

Month 4: Applications of Deep Learning

• Natural Language Processing (NLP) using Neural Networks
• Speech Recognition using Recurrent Neural Networks
• Object Detection and Image Segmentation using Deep Learning
• Time-series Analysis using RNNs
• Building and Deploying Deep Learning models in production