Foundation Model Lifecycle Explained | Pretraining vs Fine-Tuning (AWS AI Exam)

Understanding the Foundation Model Lifecycle is critical for passing the AWS AI Practitioner and Generative AI exams. In this lesson, we break down each stage of the lifecycle—from data selection and model selection to pretraining, fine-tuning, evaluation, deployment, and feedback.

You’ll clearly learn:

The difference between pretraining vs fine-tuning

What an epoch is and how it affects underfitting and overfitting

How foundation models are adapted for real-world use cases

How AWS services like Amazon SageMaker support the full model lifecycle

This video is perfect if you’re studying Generative AI, LLMs, Bedrock, or AWS certification exams and want concepts explained clearly, visually, and exam-ready.

👉 Watch till the end to lock in these high-value exam concepts.

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Видео Foundation Model Lifecycle Explained | Pretraining vs Fine-Tuning (AWS AI Exam) канала Ai Cloud Path