What you'll learn:
- Discover the fundamentals of Amazon Bedrock's AI platform, gaining a comprehensive understanding of its architecture and capabilities.
- Learn how to effectively install, configure, and utilize Amazon Bedrock's tools, including an in-depth exploration of text processing with Amazon Titan.
- Master the use of advanced AI techniques such as Retrieval Augmented Generation (RAG), and how to apply embeddings and large language models for the real world.
- Develop proficiency in extracting and processing complex information from diverse data sources, such as PDF documents and call transcripts
- Understand the principles of AI-powered text and image processing, including the exploration of Stability AI parameters and Amazon's Boto3 for image generation
- Apply your learned skills in practical, hands-on projects, including the creation of a visual recipe guide.
Welcome to this course on Amazon Bedrock. This program has been expertly crafted to immerse you in the world of Amazon's AI platform, Bedrock, emphasizing practical Python applications. Suitable for both AI novices and seasoned practitioners, this course promises to deepen your understanding and provide hands-on experience in AI.
The course journey commences with an enlightening Section 1, offering an introduction to the course layout, essential resources, and FAQs. This foundational segment is essential for equipping you with the necessary tools and knowledge about Amazon Bedrock, including detailed installation and setup instructions to kickstart your AI adventure.
In Section 2, we delve into the complexities of Amazon Bedrock's text models. You'll explore critical text processing parameters and work with Amazon Titan and Llama 2, Bedrock's advanced text modeling tools. This section combines theoretical knowledge with practical application, featuring a project on call transcript analysis and exercises to enhance your skills in extracting and processing information from PDFs.
Section 3 transports you to the fascinating world of AI-powered image generation. It covers the essentials of image creation with Stability AI parameters and Amazon's Boto3, including Titan's capabilities in this area. The section's highlight is the Recipe Code Along Project, where you will creatively and technically generate a visual recipe guide.
The course culminates in Section 4, focusing on Retrieval Augmented Generation (RAG). This advanced topic is pivotal in AI, and you'll learn about its practical applications and benefits, particularly how Amazon Bedrock integrates embeddings and large language models in RAG.
