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PyTorch Basics

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

★ 4.1 (32 ratings)3 weeksCertificate

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.

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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.
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Fee Structure

Discounted: ₹8499 | $190

We accept 20+ global currencies. View list →

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Frequently asked questions

Will I get the recording?

Yes. Paid participants get the session recordings and study material in their NanoSchool dashboard (My registrations → Recorded Lectures / Study Material).

What if I miss a live session?

Watch the recording in your dashboard and send your questions to the mentor through the support desk.

Do I get a certificate?

Yes, an e-certificate of participation after the workshop, with a QR code anyone can verify and an "Add to LinkedIn" button.

Which fee category applies to me?

Choose the category that matches your current role: Student, Ph.D. Scholar / Researcher, Academician / Faculty or Industry Professional.

How can I pay?

By card, UPI or PayPal on the payment page; international bank transfer is also available there.

What is the refund policy?

See our Returns, Refunds & Cancellation policy: Returns, Refunds & Cancellation policy

Need Help?

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