Home >Courses >PyTorch Basics

NSTC Logo
Home >Courses >PyTorch Basics

Mentor Based

PyTorch Basics

PyTorch, neural networks, AI training, deep learning, model deployment, industry applications, machine learning, real-world AI, advanced architectures

Register NowExplore Details

Early access to e-LMS included

  • Mode: Virtual / Online
  • Type: Mentor Based
  • Level: Beginners
  • Duration: 3 weeks

About This Course

PyTorch – Use in AI is an intensive course tailored for M.Tech, M.Sc, and MCA students, as well as E0 & E1 level professionals interested in mastering this powerful deep learning framework. The course covers PyTorch fundamentals, neural network construction, model training, and real-world applications, preparing participants to tackle complex AI challenges in various industries.

Aim

This course aims to provide an in-depth understanding of PyTorch, its applications in AI from basic concepts to advanced model architectures, and hands-on guidance on building and deploying neural network models.

Program Objectives

  • Mastering PyTorch: Gain comprehensive knowledge and hands-on experience with PyTorch.
  • Neural Network Proficiency: Become proficient in designing and implementing various types of neural networks.
  • Practical AI Solutions: Develop practical AI solutions that can be deployed in real-world environments.

Program Structure

  1. Introduction to PyTorch:
    • Basics of PyTorch, its comparison with other AI frameworks, and initial setup instructions.
  2. Building Blocks of Neural Networks:
    • Detailed exploration of layers, activation functions, and the construction and debugging of neural networks.
  3. Training Models:
    • In-depth coverage of loss functions, optimization algorithms, and effective training and validation techniques.
  4. Advanced PyTorch:
    • Advanced topics such as convolutional and recurrent neural networks, transfer learning, and fine-tuning.
  5. Real-World Applications:
    • PyTorch applications in industries like healthcare and autonomous vehicles, and strategies for deploying PyTorch models.
  6. Projects and Assessments:
    • A capstone project that encompasses designing, building, and presenting a PyTorch-based AI solution.

Who Should Enrol?

  • Advanced students and professionals in M.Tech, M.Sc, and MCA programs.
  • E0 & E1 level professionals in fields such as IT, BFSI, consulting, and fintech.

Program Outcomes

  • Advanced PyTorch Skills: Proficiency in using PyTorch for AI model development and deployment.
  • Industry Readiness: Preparedness to apply AI skills in real-world industry settings.
  • Innovative Thinking: Enhanced ability to innovate in AI with the latest PyTorch techniques.

Fee Structure

Discounted: ₹8499 | $190

We accept 20+ global currencies. View list →

What You’ll Gain

  • Full access to e-LMS
  • Real-world dry lab projects
  • 1:1 project guidance
  • Publication opportunity
  • Self-assessment & final exam
  • e-Certificate & e-Marksheet

Join Our Hall of Fame!

Take your research to the next level with NanoSchool.

Publication Opportunity

Get published in a prestigious open-access journal.

Centre of Excellence

Become part of an elite research community.

Networking & Learning

Connect with global researchers and mentors.

Global Recognition

Worth ₹20,000 / $1,000 in academic value.

Need Help?

We’re here for you!


(+91) 120-4781-217

★★★★★
Prediction of Protein Structure Using AlphaFold: An Artificial Intelligence (AI) Program

overall it was a good learning experience

Purushotham R V
★★★★★
AI-Powered Biosignal Analytics & Remote Patient Monitoring – Hands-on Bootcamp

really badly prepared, expected much more of this especially when basic programming knowledge is being required by participants it would be nice to learn something additional and actually discuss the topics that were announced

Franziska Singer
★★★★★
Prediction of Protein Structure Using AlphaFold: An Artificial Intelligence (AI) Program

Thank you

Jessica Grube
★★★★★
Prediction of Protein Structure Using AlphaFold: An Artificial Intelligence (AI) Program

Teaching style and slides are very old technology, low resolution. There are many new, easy to use tools, why still use very old books to show protein structures and use the paint to draw neural networks etc.

Han Kurt

View All Feedbacks →

Stay Updated


Join our mailing list for exclusive offers and course announcements

Ai Subscriber