Deep Learning With PyTorch Training in Gurgaon, Delhi

Deep Learning With PyTorch

Accelerate your deep learning with PyTorch covering all the fundamentals of deep learning with a python-first framework.

Duration : 6 months Classes : 36 Days : Weekdays / Weekends

Overview
Curriculum
Pre-requisite
Review

Dive into the dynamic world of Artificial Intelligence with our comprehensive course, "Deep Learning using PyTorch." PyTorch, renowned for its dynamic computation graph and ease of debugging, is the preferred framework for cutting-edge research and deployment in major tech labs worldwide. This program provides a rigorous, code-centric approach, empowering you to master the fundamental building blocks of Deep Neural Networks (DNNs) and implement them with the flexibility and power PyTorch offers. You will gain hands-on expertise building and training specialized architectures like Convolutional Neural Networks (CNNs) for complex image tasks and Recurrent Neural Networks (RNNs) for sequence data. Crucially, you will learn to leverage GPU acceleration and PyTorch's native C++ backend (TorchScript) to optimize models, preparing you to deploy high-performance, customized AI solutions in real-world environments.

This program offers a hands-on journey into the world of neural networks using one of the most powerful and flexible deep learning frameworks available. Learners will explore the full lifecycle of model development-from designing custom architectures to training, evaluating, and deploying models for real-world applications. With PyTorch's intuitive interface and dynamic computation graph, participants will gain the skills to experiment rapidly and scale efficiently. Whether you're tackling computer vision, natural language processing, or time-series forecasting, this course empowers you to create cutting-edge solutions with confidence and clarity.

This course blends theory with hands-on practice to help you build intelligent systems that learn and adapt. Whether you're looking to break into AI or sharpen your DL/ML toolkit, this program delivers the skills and confidence to thrive.

Target Audience:-
-Developers and engineers with basic Python and ML knowledge
-Data analysts and scientists transitioning into DNNs
-Students and professionals preparing for AI-focused careers
-Tech enthusiasts eager to explore predictive modeling and automation
-Statisticians and Mathematicians

Program Outcomes:-
-Understand the fundamentals of deep learning and PyTorch's architecture
-Build and train neural networks using PyTorch's dynamic graph and modular design
-Implement key architectures including CNNs, RNNs, LSTMs, and Transformers
-Apply optimization techniques, regularization, and learning rate scheduling
-Use PyTorch's DataLoader and Dataset APIs for efficient data handling
-Visualize training progress and debug models using TensorBoard and other tools
-Solve real-world problems in image classification, text generation, and forecasting
-Export and deploy PyTorch models using TorchScript and ONNX for production environments

Course Format:-
✔ The course shall be delivered through a combination of lectures, interactive discussions & case studies
✔ Participants are exposed to practical exercises and new-age projects, where they learn by doing
✔ Participants shall have access to online resources, including reading materials, videos & business simulations
✔ Students shall receive all the study material
✔ Guest speakers from the industry may be invited to share insights and experiences
✔ Regular assessments and quizzes will be conducted to reinforce learning
✔ This is a Classroom only training
✔ Corporates: We understand your specific needs and goals. Contact us for customizations to this training

Trainers:-
✔ Equipped with multidisciplinary backgrounds
✔ Experts from the field of Maths, Financial Markets, AIML, Data Science & Management
✔ Each with over 25+ years of International experience working in EU / US / Australia
✔ All our trainers are Highly Qualified and Certified, in their respective subject areas

-You have hands on exp with Machine Learning / Hadoop technologies with a genuine interest in Deep Learning.

- You need to know basic Python such as lists, dictionaries, loops, functions and classes

-You need to know basic differentiation

-You need to know basic algebra

....

NB: All our trainings are always tailored to adopt to the Individual's Pace and Learning Depth.

NB: As a stepping stone, providing foundational knowledge, Bridge Courses are conducted periodically, to help students transition between different levels by closing knowledge gaps. These classes can be attended ad hoc, and are 'complimentary' for our bonafide students.

Kindly fill the DownloadPDF Form for the Brouchre with latest curriculum and full Training details.
Or you may Book an Appointment to collect your Brouchre and complete your registration.

This syllabus provides a structured, module-by-module breakdown of this comprehensive training program focused on participants overall performance, retention, and engagement, covering foundational theory, implementation, best industry practices and advanced techniques in the subject.

Module 1: PyTorch Fundamentals and Core Mechanics
✔ PyTorch Setup and Tensors
✔ Tensor Operations and NumPy Bridge
✔ The Autograd System
✔ Building a Custom Training Loop
✔ Optimization and Weight Initialization

Module 2: The torch.nn Module and Model Construction
✔ The nn.Module Class
✔ Standard Layers and Loss Functions
✔ Data Loading with torch.utils.data
✔ Model Saving and Loading
✔ PyTorch vs. Keras Philosophy

Module 3: Convolutional Neural Networks (CNNs)
✔ Core CNN Layers
✔ Building a Classification CNN
✔ Image Augmentation and Data Generation
✔ Transfer Learning
✔ Visualization and Debugging

Module 4: Recurrent and Sequential Models
✔ Sequence Data and Embeddings
✔ Recurrent Neural Networks (RNNs)
✔ Gated Architectures
✔ Packed Sequences and Padding
✔ Attention Mechanism (Conceptual)

Module 5: Performance, Deployment, and Advanced Topics
✔ GPU Acceleration and Multi-GPU
✔ Optimization and Regularization
✔ Model Deployment with TorchScript
✔ TorchServe and ONNX

Module 6: Advanced Architectures and Techniques
✔ Autoencoders for dimensionality reduction
✔ Generative models with Variational Autoencoders (VAEs)
✔ Introduction to GANs using Keras
✔ Attention mechanisms and Transformer basics
✔ Integration with cloud platforms

Module 7: Capstone Project
✔ Project Scope
✔ Choose a real-world dataset and problem domain
✔ Design, train, and evaluate a deep learning model
✔ Document and present findings with visualizations

NB:The curriculum is regularly subjected to updates, reflecting the latest industry trends & current technological advancements.

At Vyom Data Sciences, we aspire to provide the latest curriculum and most recent technology, as a standard component of all our trainings. Experts, with 25+ years of experience from USA, Europe and Australia, bring the best industry practices while designing and executing these trainings. All our trainers are Highly Qualified and Certified in their respective subject areas.

Kindly fill the DownloadPDF Form for the Brouchre with latest curriculum and full Training details.
Or you may Book an Appointment to collect your Brouchre.

Bhawana

Fabulous NLP + ML course

I have eleven plus years of experience taking training courses. I do not usually complete surveys.
Your instructor was excellent, the best I've experienced on a software subject, and I couldn't imagine him doing a better job of seamlessly walking students through a breadth of information for such complex subject like AI and ML. he did a fabulous job pacing everything and addressing student questions. I am very impressed.

Harish

Excellent ML course!

The course was well structured and easy to understand. Good pace of learning.
The institute believes to provide knowledge as well as guidance in detail to each & every student.
I completed my ML course from the institute. Their international exp does help a lot !
Thanks for the training sir.