• Introduction to Data Science
• Basic Python Programming
• Python Programming – Data Science

• Introduction to Deep Learning
• Overview of deep learning and its applications
• History and Evolution of Deep Learning
• Basic concepts: neural networks, activation functions, and optimization

Artificial Neural Networks

• Perceptrons and multi-layer perceptron’s
• Forward propagation and backpropagation algorithms
• Activation functions: sigmoid, ReLU, and others
• Loss functions: mean squared error, cross-entropy, etc.

Training Deep Neural Networks

• Data preprocessing and normalization
• Gradient descent optimization algorithms
• Regularization techniques: dropout, L1/L2 regularization

Convolutional Neural Networks (CNNs)

• Introduction to CNN architecture
• Convolutional layers, pooling layers, and padding
• CNN architectures: LeNet, AlexNet, VGG, ResNet
• Transfer learning and fine-tuning

Recurrent Neural Networks (RNNs)

• Introduction to RNNs and their Applications
• Backpropagation through time (BPTT)
• Long Short-Term Memory (LSTM) networks
• Gated Recurrent Units (GRUs)

Advanced Deep Learning Techniques

• Generative Adversarial Networks (GANs)
  Autoencoders and variational autoencoders (VAEs)
• Reinforcement learning with deep neural networks
• Attention mechanisms and transformer models

• Word embeddings: Word2Vec, GloVe
• Recurrent models for language modeling and text generation
• Sequence-to-sequence models and machine translation
• Transformer models: BERT, GPT, and their applications

• Overview of popular deep learning frameworks (TensorFlow, PyTorch)
• Hands-on exercises and coding examples
• Deployment and inference on GPUs or cloud platforms

• Age and Gender Detection with Deep Learning for Real-Time Applications
• BitCoin Price Prediction
• Automatic Parking Vehicle Verification and Parking System using Number Plate Recognition
• Person Counting System using Deep Learning
• Vehicle Speed Estimation
• Face Recognition
• Automatic Multi-Class Classification of Food Ingredients using Deep Learning
• Detection Algorithms in Deep Learning
• Fire Detection Using Flame Detector in Deep Learning
• Image-to-Text, Text-to-Speech Conversion
• Social Distance Detection
• Handwritten Recognition using Deep Features
• Head Pose Estimation in the Wild Using Convolutional Neural Networks and Adaptive Gradient Methods
• Driver Drowsiness and Yawn Detection
• Drone Detection using OpenCV
• Face Emotion Detection
• Automatic Leaf Characteristics Detection using Neural Network
• Face Recognition using OpenCV and Deep Learning
• Yolo Object Detection Using OpenCV Technique
• Face Clustering using DL
• Covid -19 chest X-ray images detection using dl
• Smart Glasses and sign Language Based Hand Gesture Recognition
• Optical Character Recognition using OpenCV