Course Overview:

Deep learning is transforming industries by enabling machines to learn complex patterns from data. From healthcare to retail and automotive, deep learning powers applications like image recognition, speech processing, and language translation. This course introduces the core concepts of deep learning through practical, hands-on exercises. Learners will build and train models using real-world datasets, apply data augmentation, and explore transfer learning techniques to accelerate development. By the end of the course, participants will be equipped with the foundational skills to begin their deep learning journey. 

After completing this course, participants will be able to:

  • Understand the fundamental techniques and tools used in deep learning.
  • Work with common data types and model architectures.
  • Apply data augmentation to improve model performance.
  • Use transfer learning to build efficient models with limited data.
  • Deploy and test deep learning models in real-world scenarios.
  • Gain confidence to start your own deep learning projects using modern frameworks.

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Key Features of Getting Started with Deep Learning:

  • Hands-on labs in computer vision and NLP.

  • Training with real-world datasets.

  • Use of PyTorch and pre-trained models.

  • Practical deployment and prediction exercises.

  • Certificate of completion from NVIDIA DLI.

  • Access to additional learning resources and related courses.

Who should Attend?

  • Beginners in AI and deep learning
  • Developers and data scientists exploring machine learning
  • Students and professionals transitioning into AI roles
  • Anyone interested in building foundational deep learning skills

Prerequisites of Getting Started with Deep Learning:

  • Basic programming knowledge in Python 3 (functions, loops, dictionaries, arrays)
  • Familiarity with Pandas data structures
  • Understanding of regression concepts
  • (Optional) Completion of “Building a Brain in 10 Minutes” for historical context on neural networks

    • Why choose CloudThat as your training partner?

    • Foundational Deep Learning Focus: CloudThat offers beginner-friendly, hands-on training designed to help learners build a strong foundation in deep learning concepts and applications.
    • Industry-Recognized Trainers: Our instructors are certified professionals with real-world experience in computer vision, NLP, and AI model deployment using frameworks like PyTorch.
    • Hands-On Learning Approach: The course includes practical exercises in image classification, data augmentation, transfer learning, and NLP using real datasets and pre-trained models.
    • Customized Learning Paths: Whether you're new to AI or transitioning from another tech domain, our training adapts to your pace and learning goals.
    • Interactive Learning Experience: Engage in live sessions, Q&A, and mentorship that make complex deep learning topics easier to grasp and apply.
    • Placement Assistance and Career Support: We support learners with resume building, interview preparation, and job placement opportunities in AI and data science roles.
    • Continuous Learning and Updates: Our curriculum is regularly updated to reflect the latest tools, frameworks, and best practices in deep learning.
    • Positive Reviews and Testimonials: Trusted by thousands of learners and enterprises, CloudThat is known for delivering impactful and accessible AI training.

    Course Outline: Download Course Outline

    • The MNIST Dataset.
    • Tensors.
    • Preparing the Data for Training.
    • Creating the Model.
    • Training the Model.

    • The American Sign Language Dataset.
    • Loading the Data.
    • Visualizing the Data.
    • Build the Model.
    • Training the Model.

    • Loading and Preparing the Data.
    • Creating a Convolutional Model.
    • Summarizing the Model.
    • Training the Model.

    • Preparing the Data.
    • Model Creation.
    • Data Augmentation.
    • Training with Augmentation.
    • Saving the Model.

    • Loading the Model.
    • Preparing an Image for the Model.
    • Making Predictions.

    • An Automated Doggy Door.
    • Loading the Model.
    • Loading an Image.
    • Make a Prediction.
    • Only Dogs

    • Personalized Doggy Door.
    • Data Augmentation.
    • The Training Loop.
    • Fine-Tuning the Model.

    • BERT.
    • Tokenization.
    • Segmenting Text.
    • Text Masking.
    • Question and Answering.

    Certification Details:

      Participants who complete the course and hands-on labs will receive an official NVIDIA Deep Learning Institute Certificate of Completion for Getting Started with Deep Learning.

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    Course ID: 26330

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    FAQs:

    No prior deep learning experience is required. A basic understanding of Python and data structures is sufficient.

    The course uses PyTorch, Pandas, and pre-trained models for hands-on exercises.

    Yes, upon successful completion, you will receive an NVIDIA DLI Certificate of Completion.

    The course is priced at $90.

    This course provides a strong foundation for roles in AI development, machine learning engineering, and data science.

    Enquire Now