Course Overview:

This NVIDIA Deep Learning Institute (DLI) course provides a solid foundation in deep learning techniques tailored for computer vision. Participants will explore the mechanics of convolutional neural networks (CNNs), leverage pre-trained models, and apply transfer learning to accelerate development. Through guided labs and a final project, learners will build and optimize models for object recognition and classification tasks.

After completing this course, participants will be able to:

  • Understand the architecture and training process of convolutional neural networks (CNNs).
  • Implement data augmentation to improve model generalization.
  • Apply transfer learning using pre-trained models to solve vision problems.
  • Explore recurrent neural networks (RNNs) for sequential data tasks.
  • Design, train, and deploy deep learning models for image classification.

Upcoming Batches

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Key Features:

  • Instructor-led training with NVIDIA-certified DLI instructors.

  • Hands-on practice using GPU-powered cloud labs.

  • Step-by-step guidance through real-world projects.

  • Exposure to TensorFlow and PyTorch frameworks.

  • Industry-recognized NVIDIA DLI certificate upon completion.

Who should Attend?

  • Data scientists and machine learning engineers.
  • AI enthusiasts aiming to start or advance in deep learning.
  • Developers working on computer vision applications.
  • Students and researchers in AI/ML domains.

Prerequisites:

  • An understanding of fundamental programming concepts in Python 3, such as functions, loops, dictionaries, and arrays; familiarity with Pandas data structures; and a basic understanding of how to compute a regression line.

    • Why choose CloudThat as your training partner?

    • Authorized NVIDIA DLI Training Partner delivering globally recognized courses.
    • Expert Trainers with hands-on project and industry experience.
    • Hands-on Learning with GPU-powered labs and real-world projects.
    • Career-Oriented Guidance with placement support and mentorship.
    • Flexible Training Models: Online, classroom, or corporate batches.
    • Proven Track Record: Trusted by 650+ corporates and 100K+ learners worldwide.

    Course Outline: Download Course Outline

    • Meet the instructor.
    • Create an account at courses.nvidia.com/join

    Explore the fundamental mechanics and tools involved in successfully training deep neural networks:

    • Train your first computer vision model to learn the process of training.
    • Introduce convolutional neural networks to improve accuracy of predictions in vision applications.
    • Apply data augmentation to enhance a dataset and improve model generalization.

    Leverage pre-trained models to solve deep learning challenges quickly. Train recurrent neural networks on sequential data:

    • Integrate a pre-trained image classification model to create an automatic doggy door.
    • Leverage transfer learning to create a personalized doggy door that only lets in your dog.
    • Use a Large Language Model (LLM) to answer questions based on provided text.

    Apply computer vision to create a model that distinguishes between fresh and rotten fruit:

    • Create and train a model that interprets color images.
    • Build a data generator to make the most out of small datasets.
    • Improve training speed by combining transfer learning and feature extraction.
    • Discuss advanced neural network architectures and recent areas of research where students can further improve their skills.

    • Review key learnings and answer questions.
    • Complete the assessment and earn a certificate.
    • Complete the workshop survey.
    • Learn how to set up your own AI application development environment.

    Certification Details:

      Participants who successfully complete all modules and the final assessment will receive an official NVIDIA DLI Certificate of Competency in “Fundamentals of Deep Learning.”

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    Course ID: 26364

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    FAQs:

    No. Basic Python programming and machine learning knowledge is sufficient.

    The course primarily uses PyTorch and TensorFlow, running on GPU-powered labs.

    Labs are accessible during and shortly after the course; however, lifetime access is not included.

    An NVIDIA Deep Learning Institute (DLI) Certificate of Competency for “Fundamentals of Deep Learning.”

    Enquire Now