Course Overview
This intensive bootcamp is designed for individuals looking to gain a comprehensive understanding of Deep Learning, its fundamental concepts, and practical applications in Artificial Intelligence and Machine Learning. We cover everything from the theoretical underpinnings of neural networks to building and deploying complex models.
What You'll Learn:
- The mathematics behind Deep Learning (Linear Algebra, Calculus, Probability)
- Building blocks of Neural Networks (Perceptrons, Activation Functions)
- Deep Neural Networks and Backpropagation
- Convolutional Neural Networks (CNNs) for image recognition
- Recurrent Neural Networks (RNNs) and LSTMs for sequence data
- Transformers and attention mechanisms
- Practical implementation using TensorFlow and PyTorch
- Model optimization, regularization, and hyperparameter tuning
- Ethical considerations and future trends in AI
Prerequisites:
- Basic understanding of Python programming
- Familiarity with fundamental Machine Learning concepts (supervised/unsupervised learning)
- Comfort with mathematical concepts
