English | MP4 | AVC 1920×1080 | AAC 44KHz 2ch | 37 Lessons (3h 28m) | 811 MB
Learn the cutting-edge world of AWS Bedrock and gain skills to create AI apps. You’ll build and deploy three AI projects using foundation models from Meta, Anthropic, Cohere, Mistral and more, all from a single API!
This course is made for anyone eager to take dive deep into building AI-driven applications using the latest technologies. By the end of this course you’ll have a comprehensive understanding of AWS Bedrock and Generative AI, including Retrieval Augmented Generation (RAG), fine-tuning, vector databases, word embeddings, serverless architecture, training and evaluation of LLMs with your own custom data, and more!
WHAT YOU’LL LEARN
- Gain insights into AWS Bedrock and LLMs, positioning yourself at the forefront of AI innovation
- Build a theoretical and practical foundation in AI, encompassing everything from LLMs to Diffusion Models
- Apply knowledge through projects like chatting with data, coding with foundational models, and image generation
- Acquire skills in serverless architecture integration and deployment using AWS services including AWS Bedrock, API Gateway, Lambda functions, S3, Postman, and more
- Learn to fine-tune and evaluate LLMs for ethical and effective AI solutions
- Position yourself as a valuable asset in the evolving AI industry
- Get hands-on experience with AWS services, directly transferable to professional settings
- Develop critical thinking and problem-solving skills in AI project design and execution, preparing you for complex challenges in the tech field
Table of Contents
1 Introduction
2 What We’re Buildin
3 Setting Up our AWS Accoun
4 Login to IAM User Accoun
5 What is AWS Bedrock
6 Introduction to Foundational Model
7 Foundational Model Provider
8 Bedrock Playground and Pricin
9 Inspecting Model Inference Configurations for LLMs and Image Generation Model
10 Training Foundation Models with your Custom Dat
11 Setting Up the Code Generation Projec
12 Coding our Lambda Function and Integrating with AWS Bedroc
13 Setting up API Gateway and our Serverless Stac
14 Testing our Live Endpoin
15 Creating our Boto3 Lambda Laye
16 Attaching our Lambda Layer to our Functio
17 Testing our Bedrock Mode
18 Verifying Final Output of Bedroc
19 Setting up our Lambda Function with Bedrock for Content Summarizatio
20 Finishing our Lambda Function for Meeting Summarisatio
21 Creating new API Gateway Endpoint for this Lambda Functio
22 Invoking our Serverless Meeting Notes Summarisation Endpoin
23 Analyzing the Final Result
24 Project Introductio
25 Setting up API Gateway Route (Serverless) for New Generative AI Model Invocatio
26 Invoking our Stable Diffusion model for Image Generatio
27 Analysing our Final Outpu
28 Set up Evaluation Job for Anthropic’s Claude mode
29 Evaluating our Results
30 Introduction to AWS Bedrock Knowledge Bas
31 Retrieval Augmented Retrieval (RAG) Overvie
32 Setting Up Our Own Knowledge Base – Part
33 Setting Up Our Own Knowledge Base – Part
34 Testing our Bedrock Knowledge Base with Antropic’s Claude Model
35 Clean Up Resource
36 API Resource
37 A Little Cleanup and Congratulations
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