New technical deep dive course: Generative AI Foundations on AWS
Generative AI Foundations on AWS is a brand new technical deep dive course that offers you the conceptual fundamentals, sensible recommendation, and hands-on steerage to pre-train, fine-tune, and deploy state-of-the-art basis fashions on AWS and past. Developed by AWS generative AI worldwide foundations lead Emily Webber, this free hands-on course and the supporting GitHub supply code launched through AWS Youtube. If you’re searching for a curated playlist of the highest sources, ideas, and steerage to stand up to hurry on basis fashions, and particularly people who unlock generative capabilities in your information science and machine studying tasks, then look no additional.
Throughout this 8-hour deep dive, you may be launched to the important thing strategies, companies, and tendencies that can assist you perceive basis fashions from the bottom up. This implies breaking down concept, arithmetic, and summary ideas mixed with hands-on workouts to achieve useful instinct for sensible software. All through the course, we deal with a large spectrum of progressively complicated generative AI strategies, providing you with a robust base to grasp, design, and apply your individual fashions for the most effective efficiency. We’ll begin with recapping basis fashions, understanding the place they arrive from, how they work, how they relate to generative AI, and what you may to do customise them. You’ll then study selecting the correct basis mannequin to fit your use case.
When you’ve developed a robust contextual understanding of basis fashions and the right way to use them, you’ll be launched to the core topic of this course: pre-training new basis fashions. You’ll be taught why you’d wish to do that in addition to how and the place it’s aggressive. You’ll even learn to use the scaling legal guidelines to select the fitting mannequin, dataset, and compute sizes. We’ll cowl getting ready coaching datasets at scale on AWS, together with selecting the correct situations and storage strategies. We’ll cowl fine-tuning your basis fashions, evaluating latest strategies, and understanding the right way to run these along with your scripts and fashions. We’ll dive into reinforcement studying with human suggestions, exploring the right way to use it skillfully and at scale to really maximize your basis mannequin efficiency.
Lastly, you’ll learn to apply concept to manufacturing by deploying your new basis mannequin on Amazon SageMaker, together with throughout a number of GPUs and utilizing high design patterns like retrieval augmented era and chained dialogue. As an added bonus, we’ll stroll you thru a Steady Diffusion deep dive, immediate engineering greatest practices, standing up LangChain, and extra.
Extra of a reader than a video client? You may try my 15-chapter e book “Pretrain Imaginative and prescient and Massive Language Fashions in Python: Finish-to-end strategies for constructing and deploying basis fashions on AWS,” which launched Could 31, 2023, with Packt publishing and is on the market now on Amazon. Wish to leap proper into the code? I’m with you—each video begins with a 45-minute overview of the important thing ideas and visuals. Then I’ll provide you with a 15-minute walkthrough of the hands-on portion. All the instance notebooks and supporting code will ship in a public repository, which you should use to step by by yourself. Be at liberty to achieve out to me on Medium, LinkedIn, GitHub, or by your AWS groups. Be taught extra about generative AI on AWS.
Completely happy trails!
Course define
1. Introduction to Basis Fashions
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2. Choosing the right basis mannequin
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3. Utilizing pretrained basis fashions: immediate engineering and fine-tuning
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4. Pretraining a brand new basis mannequin
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5. Getting ready information and coaching at scale
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6. Reinforcement studying with human suggestions
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7. Deploying a basis mannequin
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Concerning the creator
Emily Webber joined AWS simply after SageMaker launched, and has been attempting to inform the world about it ever since! Outdoors of constructing new ML experiences for purchasers, Emily enjoys meditating and learning Tibetan Buddhism.
