To be Scheduled

Deep Learning & AI Applications: From Neural Networks to Intelligent Systems

Learn to design and deploy neural networks and deep learning models for real-world AI applications. Gain hands-on experience with Python, TensorFlow, and Keras to build intelligent systems that solve complex problems.

To be Scheduled_Weekends Only

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About this Training

This hands-on training covers the principles and applications of deep learning and artificial intelligence. Participants will explore neural network architectures, CNNs, RNNs, and advanced models for computer vision, NLP, and predictive analytics. The course emphasizes practical exercises with Python, TensorFlow, and Keras, allowing learners to implement, train, and optimize deep learning models. By the end of the program, participants will be capable of designing AI solutions, evaluating model performance, and deploying intelligent systems for research, business, and technology applications.

What You'll Learn

Module 1: Introduction to Deep Learning – Fundamentals of neural networks and deep learning concepts
Module 2: Neural Network Architectures – Feedforward convolutional recurrent and transformer networks
Module 3: Data Preparation & Preprocessing – Normalization encoding and dataset splitting for training
Module 4: Model Training & Optimization – Backpropagation loss functions and optimization techniques
Module 5: Computer Vision Applications – CNNs image classification and object detection
Module 6: Natural Language Processing (NLP) – RNNs transformers and text data modeling
Module 7: Model Evaluation & Deployment – Metrics overfitting handling and deploying models
Module 8: Real-World Projects – Building AI solutions for real datasets and applications

This training includes:

Hands-on exercises with neural networks

Model training and optimization practice

Data preprocessing for deep learning

Implementing CNNs for computer vision tasks

NLP modeling and text data projects

Evaluation and performance tuning

Deploying AI models

Real-world projects to consolidate skills

Skills you'll gain:

Neural network design and implementation

Deep learning model training and optimization

CNNs for computer vision

RNNs and transformers for NLP

Data preprocessing and handling for AI

Model evaluation and performance tuning

AI model deployment

Solving real-world problems with deep learning