Generative AI on AWS: Building GenAI Models with Amazon SageMaker

Generative AI    |    Intermediate
  • 14 videos | 1h 35m 38s
  • Includes Assessment
  • Earns a Badge
Rating 5.0 of 1 users Rating 5.0 of 1 users (1)
This comprehensive course introduces learners to the world of generative artificial intelligence (AI) models within machine learning (ML), focusing on Amazon SageMaker as a prime tool for design, training, optimization, deployment, and monitoring. In this course, we will begin with a deep dive into the fundamental concepts and types of generative models like generative adversarial networks (GANs) and variational autoencoders (VAEs). We will explore their pros, cons, and relevant architectures. Next, we will use hands-on tutorials and in-depth discussions to guide you through the steps of designing a GAN architecture, leveraging SageMaker's built-in algorithms, preprocessing data, and distributed training capabilities. We will then delve into optimization techniques, transfer learning, and quality evaluation methods, looking at ways apply these concepts in real-world scenarios. Lastly, we will introduce deployment strategies in SageMaker, highlighting how to serve models as endpoints for real-time inferences and how to efficiently monitor and troubleshoot their generative models.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Outline the fundamental concepts of generative models and their applications in machine learning
    Analyze the different types of generative models, including generative adversarial networks (gans) and variational autoencoders (vaes)
    Compare and contrast the pros and cons of various generative model architectures
    Design and implement a gan architecture using amazon sagemaker
    Preprocess and prepare data for training generative models in sagemaker
    Utilize sagemaker's built-in algorithms for training generative models
  • Train a generative model using sagemaker's distributed training capabilities
    Fine-tune and optimize generative models in sagemaker for improved performance
    Apply transfer learning techniques to adapt pre-trained generative models to specific domains
    Evaluate the quality and diversity of generated content using appropriate metrics
    Deploy and serve generative models as endpoints in sagemaker for real-time inference
    Monitor and troubleshoot generative model training and deployment processes in sagemaker
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 27s
    In this video, we will discover the key concepts covered in this course. FREE ACCESS
  • 5m 54s
    After completing this video, you will be able to outline the fundamental concepts of generative models and their applications in machine learning. FREE ACCESS
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    3.  Types of Generative Models: GANs and VAEs
    6m 47s
    In this video, we will Analyze the different types of generative models, including generative adversarial networks (GANs) and variational autoencoders (VAEs). FREE ACCESS
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    4.  Comparing Generative Model Architectures
    7m 30s
    Upon completion of this video, you will be able to Compare and contrast the pros and cons of various generative model architectures. FREE ACCESS
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    5.  Designing GANs with Amazon SageMaker
    7m 12s
    In this video, find out how to design and implement a GAN architecture using Amazon SageMaker. FREE ACCESS
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    6.  Performing Data Preprocessing for Generative Models in SageMaker
    5m 48s
    Find out how to preprocess and prepare data for training generative models in SageMaker. FREE ACCESS
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    7.  Training Generative Models with SageMaker Algorithms
    9m 24s
    During this video, discover how to utilize SageMaker's built-in algorithms for training generative models. FREE ACCESS
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    8.  Executing Distributed Training of Generative Models in SageMaker
    7m 19s
    Learn how to train a generative model using SageMaker's distributed training capabilities. FREE ACCESS
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    9.  Optimizing and Fine-tuning Generative Models in SageMaker
    14m 40s
    In this video, you will learn how to fine-tune and optimize generative models in SageMaker for improved performance. FREE ACCESS
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    10.  Applying Transfer Learning for Generative Models in Specific Domains
    7m 42s
    Discover how to apply transfer learning techniques to adapt pre-trained generative models to specific domains. FREE ACCESS
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    11.  Evaluating Generated Content Quality and Diversity
    7m 52s
    In this video, find out how to evaluate the quality and diversity of generated content using appropriate metrics. FREE ACCESS
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    12.  Deploying Generative Models in SageMaker for Real-time Inference
    5m 31s
    Learn how to deploy and serve generative models as endpoints in SageMaker for real-time inference. FREE ACCESS
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    13.  Monitoring Generative Models in SageMaker
    7m 27s
    Discover how to monitor and troubleshoot generative model training and deployment processes in SageMaker. FREE ACCESS
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    14.  Course Summary
    1m 5s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

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