Deep Learning – Self Paced

Master the future of Artificial Intelligence with our Deep Learning course, designed as per the latest AICTE norms. This advanced program covers the foundations of neural networks, optimization techniques, CNNs, RNNs, NLP, and generative models — preparing you for careers in AI, Data Science, and Machine Learning engineering.

The course begins with the Foundations of Deep Learning, explaining the difference between machine learning and deep learning, artificial neural networks (ANNs), perceptrons, multilayer perceptrons (MLPs), activation functions (Sigmoid, Tanh, ReLU), cost functions, and optimization basics with gradient descent and backpropagation.

In Neural Network Optimization, you’ll learn loss functions (Cross-Entropy, MSE), weight initialization, batch normalization, dropout, optimizers (SGD, Adam, RMSProp), handling overfitting/underfitting, and hyperparameter tuning.

The program dives into Convolutional Neural Networks (CNNs), exploring convolution operations, pooling techniques, and CNN architectures like LeNet, AlexNet, VGG, and ResNet. You’ll also practice transfer learning for real-world applications such as image classification and object detection.

In Recurrent Neural Networks (RNNs), you’ll study architectures, vanishing/exploding gradients, LSTMs, GRUs, and applications in time series forecasting, speech recognition, and text analytics.

A dedicated module on Natural Language Processing with Deep Learning covers embeddings (One-hot, Word2Vec, GloVe), sequence modeling, attention mechanism, Transformers, and BERT, with hands-on projects in text classification and sentiment analysis.

The final section, Generative Deep Learning, introduces Autoencoders, Variational Autoencoders (VAEs), and Generative Adversarial Networks (GANs). You’ll explore applications in image generation, deep fakes, and ethical considerations in AI.

Tools & Frameworks Covered: Python, NumPy, Pandas, Matplotlib, TensorFlow, Keras, PyTorch (optional), and Jupyter Notebooks.

By the end of this course, you’ll be equipped with industry-ready deep learning skills to build, optimize, and deploy advanced AI models, unlocking opportunities in top AI-driven industries.