Ultimate AWS Bedrock Guide: Build and Scale Generative AI Apps

3h 28m 1s
English
Paid

Course description

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!

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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!

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# Title Duration
1 Introduction 01:01
2 What We're Building 04:44
3 Setting Up our AWS Account 05:25
4 Login to IAM User Account 04:24
5 What is AWS Bedrock? 09:06
6 Introduction to Foundational Models 04:33
7 Foundational Model Providers 11:03
8 Bedrock Playground and Pricing 14:03
9 Inspecting Model Inference Configurations for LLMs and Image Generation Models 10:36
10 Training Foundation Models with your Custom Data 07:34
11 Setting Up the Code Generation Project 01:06
12 Coding our Lambda Function and Integrating with AWS Bedrock 17:52
13 Setting up API Gateway and our Serverless Stack 05:35
14 Testing our Live Endpoint 05:58
15 Creating our Boto3 Lambda Layer 02:24
16 Attaching our Lambda Layer to our Function 02:25
17 Testing our Bedrock Model 06:29
18 Verifying Final Output of Bedrock 02:25
19 Setting up our Lambda Function with Bedrock for Content Summarization 08:44
20 Finishing our Lambda Function for Meeting Summarisation 14:11
21 Creating new API Gateway Endpoint for this Lambda Function 02:16
22 Invoking our Serverless Meeting Notes Summarisation Endpoint 06:31
23 Analyzing the Final Results 01:40
24 Project Introduction 10:58
25 Setting up API Gateway Route (Serverless) for New Generative AI Model Invocation 01:07
26 Invoking our Stable Diffusion model for Image Generation 03:49
27 Analysing our Final Output 00:47
28 Set up Evaluation Job for Anthropic's Claude model 04:38
29 Evaluating our Results 05:26
30 Introduction to AWS Bedrock Knowledge Base 02:58
31 Retrieval Augmented Retrieval (RAG) Overview 06:41
32 Setting Up Our Own Knowledge Base - Part 1 08:09
33 Setting Up Our Own Knowledge Base - Part 2 00:51
34 Testing our Bedrock Knowledge Base with Antropic's Claude Model 07:21
35 Clean Up Resources 01:11
36 API Resources 00:43
37 A Little Cleanup and Congratulations! 03:17

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