Torch Training and Certification in USA

This course provides an in-depth introduction to Torch, a powerful deep learning framework known for its flexibility and ease of use in training neural networks. Participants will learn how to build, train, optimize, and deploy deep learning models using Torch, covering key topics like tensor operations, automatic differentiation, neural network design, and model deployment.

Welcome to the official Torch Training and Certification certification program. This comprehensive training is designed to elevate your professional skills and provide you with practical, industry-relevant knowledge in in USA. As a globally recognized corporate training provider operating in 55+ countries, ProgNXT ensures that our curriculum meets the highest standards of excellence.

Whether you are looking to upskill your team or advance your personal career, our expert-led sessions will guide you through the core concepts of this domain. Upon successful completion of the 14 Hrs program, participants will receive a globally accepted certification, demonstrating their proficiency and readiness to tackle complex challenges in the field.

• Basic proficiency in Python or Lua (Torch's primary language)
• Understanding of machine learning and deep learning concepts
• Familiarity with Neural Networks (CNNs, RNNs, LSTMs, etc.)
• Experience with basic linear algebra and matrix operations

• Hands-on experience with Torch tensor operations
• Building and training neural networks using Torch’s NN package
• Implementing backpropagation and automatic differentiation
• Optimizing models using Torch optimizers and learning rate scheduling
• Deploying models using Torch’s scripting and serialization tools

By the end of the course, participants will be able to:

• Understand Torch’s architecture and core libraries
• Perform efficient tensor operations and automatic differentiation
• Build and train deep learning models using Torch
• Optimize model performance using loss functions and optimizers
• Deploy trained models for real-world applications