Deep Learning

1. Python Programming : 14 Hours Approx

Introduction to Python
Variables, data types, and basic operations
Control structures (loops, conditional statements)
Functions and modules
Object-oriented programming in Python

2. Introduction to Neural Networks : 10 Hours Approx.

Biological inspiration for artificial neural networks
Perceptrons and activation functions
Forward propagation and backpropagation algorithms
Loss functions and gradient descent

3. Deep Learning Frameworks : 18 Hours Approx

Introduction to deep learning libraries/frameworks (e.g., TensorFlow, Keras, PyTorch)
Installation and setup of a deep learning environment
Code examples using TensorFlow, Keras, or PyTorch

4. Convolutional Neural Networks (CNNs) : 10 Hours Approx

Architecture and working principles of CNNs.
Convolutional layers, pooling layers, and activation functions.
Training and fine-tuning CNN models.
Object detection and image segmentation with CNNs.

5. Recurrent Neural Networks (RNNs) : 10 Hours Apporx.

Introduction to sequential data and recurrent neural networks.
Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) cells.
Training and generating sequences with RNNs.
Applications of RNNs in natural language processing and time series analysis

6. Generative Adversarial Networks (GANs) : 10 Hours Approx

Overview of GANs and their components (generator and discriminator).
Training GANs using adversarial learning.
Generating synthetic images and data with GANs.
Conditional GANs and style transfer.

7. Transfer Learning : 8 Hours Approx.

Leveraging pre-trained models for transfer learning
Fine-tuning and feature extraction from pre-trained models
Hyperparameter tuning and model evaluation techniques.
Real-world applications of transfer learning

8. Advanced Deep Learning Topics : 20 Hours Approx.

Attention mechanisms and transformers.
Reinforcement learning with deep neural networks.
Deep reinforcement learning algorithms (e.g., DQN, A3C)
Explainability and interpretability in deep learning models

Capstone Project: 40 Hours

Apply deep learning techniques learned throughout the curriculum to build a significant project or
solve a specific problem.

Empowering Minds to Shape the Future with Deep Learning

Join us to unlock the power of Deep Learning and transform your future. Gain cutting-edge knowledge, hands-on experience, and expert training to master AI technologies. With practical projects and industry-leading tools like TensorFlow and PyTorch, you’ll be equipped to drive innovation and shape the future of AI.