Generative AI on AWS: Building GenAI Models with Amazon SageMaker
Generative AI
| Intermediate
- 14 videos | 1h 35m 38s
- Includes Assessment
- Earns a Badge
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
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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
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1m 27sIn this video, we will discover the key concepts covered in this course. FREE ACCESS
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5m 54sAfter 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 VAEs6m 47sIn 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 Architectures7m 30sUpon 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 SageMaker7m 12sIn 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 SageMaker5m 48sFind 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 Algorithms9m 24sDuring 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 SageMaker7m 19sLearn 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 SageMaker14m 40sIn 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 Domains7m 42sDiscover 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 Diversity7m 52sIn 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 Inference5m 31sLearn 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 SageMaker7m 27sDiscover how to monitor and troubleshoot generative model training and deployment processes in SageMaker. FREE ACCESS
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14. Course Summary1m 5sIn this video, we will summarize the key concepts covered in this course. FREE ACCESS
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