Complete AWS Bedrock Generative AI Course + Projects

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Patrik Szepesi

3:15:53

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1 - Course Introduction

1 - What We are Going to Be Building.mp4

05:26

2 - Github Link to all Code and Resources.html

2 - Initial Setup

3 - Setting Up our AWS account.mp4

05:47

4 - Login to IAM user account.mp4

04:36

3 - Getting started with Aws Bedrock

5 - What is AWS Bedrock.mp4

10:30

6 - Introduction to Foundational Models.mp4

05:01

7 - Foundational Model Providers.mp4

12:49

8 - Bedrock Playground and Pricing.mp4

16:38

9 - Inspecting Model Inference Configurations for LLMs and Image Generation Models.mp4

12:05

10 - Training Foundation Models with your Custom data.mp4

09:06

4 - Code Generation Project

11 - Setting Up the Code Generation Project.mp4

01:06

12 - Coding our Lambda function and integrating it with AWS Bedrock.mp4

21:09

13 - Setting up API Gateway and our Serverless Stack.mp4

07:01

14 - Testing our Live Endpoint.mp4

08:16

15 - Creating our Boto3 Lambda Layer.mp4

02:33

16 - Attaching our Lambda Layer to our Function.mp4

02:42

17 - Testing our Bedrock Model.mp4

07:41

18 - Verifying Final Output of Bedrock.mp4

02:53

5 - Meeting Notes Summarisation Project with Bedrock

19 - Setting up our Lambda Function with Bedrock for content summarisation.mp4

09:57

20 - Finishing our Lambda Function for Meeting Summarisation.mp4

16:06

21 - Creating new API Gateway Endpoint for this Lambda function.mp4

02:23

22 - Invoking our Serverless Meeting Notes Summarisation Endpoint.mp4

07:17

23 - Analysing the final results.mp4

01:52

6 - Using Diffusion Models with Bedrock for Image Creation

24 - Project Introduction.mp4

12:10

25 - Setting up API Gateway RouteServerless for New Generative AI Model Invocation.mp4

01:05

26 - Invoking our Stable Diffusion model for Image Generation.mp4

04:44

27 - Analysing our Final output.mp4

00:49

7 - Cleanup and Next Steps

28 - Final Video.mp4

04:11

Description

Chat with Documents, Fine-Tune LLMs, Image Diffusion Models + Generative AI Deployed with Serverless Architecture

What You'll Learn?

AWS Bedrock
Chat with your Documents
Generative AI
Build Serverless Machine Learning applications
Fine Tune LLMs in the cloud
Build production ready applications with Aws Serverless stack such as Bedrock, Lambda and Api Gateway and S3
Train and Evaluate LLMs with your own custom data
AWS Bedrock Pricing
Summarise your meeting notes in a matter of seconds
Serverless Architecture
API Gateway
Image Generation
Text Summarisation with NLP
Text Creation through NLP
Stability AI and diffusion models for image generation
Anthropic AI
Connect your data in S3 with AWS Bedrock
Set up Lambda Layers

Who is this for?

Anyone(with a little programming knowledge) who wants to learn Generative AI on AWS

What You Need to Know?

little Python knowledge

AWS account

Computer with WIFI

More details

Description
Course Description: AWS Bedrock Generative AI + LLMs Comprehensive Guide

Welcome to our in-depth course on the cutting-edge world of AWS Bedrock Generative AI, encompassing LLMs (Large Language Models) and fine-tuning techniques. AWS Bedrock, the innovative platform from Amazon Web Services, provides unparalleled opportunities for AI enthusiasts, developers, and professionals to engage with Generative AI. In this course, you will explore the nuts and bolts of AWS Bedrock and learn how to harness its power for your AI projects. Create 3 separate projects in this course which include chatting with your data and asking questions about your documents, writingÂ code with Bedrock models, and image generation with diffusion models. All these projects will be then deployed through a Serverless architecture with AWS Bedrock, API Gateway, Lambda functions, S3,Â Postman and many more

Structured over a series of engaging modules, you will:

1. Delve Deep into AWS Bedrock & Generative AI: Understand the foundations of AWS Bedrock and its role in the AI landscape. Discover the transformative potential of Generative AI, how it's shaping industries, and its underlying technologies.

2. Mastering LLMs: Dive into the intricacies of Large Language Models. Learn about their architecture, applications, strengths, and limitations.

3. Fine-tuning Models: A pivotal skill for any AI practitioner. Acquire hands-on experience in tweaking existing models to fit specific tasks or datasets, ensuring optimal performance and efficiency.

4. Hands-on Projects: Roll up your sleeves and immerse yourself in three separate projects. Each project is designed to reinforce your learning and provide practical experience. You'll employ a serverless stack, integrating AWS services like API Gateway and Lambda with AWS Bedrock, offering you a holistic view of the platform's capabilities.

5. Serverless Stack Integration: Delve into the Serverless paradigm, focusing on API Gateway, Lambda, and AWS Bedrock. Learn how to set up, manage, and scale serverless architectures seamlessly, ensuring you're well-equipped to design and deploy AI-driven applications with ease.

By the end of this course, you will have a robust understanding of AWS Bedrock and its synergies with Generative AI and LLMs. Whether you're an aspiring AI developer, a seasoned practitioner, or a tech enthusiast, this course is tailored to equip you with the skills and knowledge to navigate the dynamic world of AI with confidence.

Join us on this enlightening journey through AWS Bedrock and discover the future of Generative AI. Let's build, fine-tune, and deploy together!
Who this course is for:
Anyone(with a little programming knowledge) who wants to learn Generative AI on AWS

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I am an AWS certified machine learning engineer , working as a machine learning engineer at Blue River Technology, a Silicon Valley company creating computer vision machine learning solutions(such as autonomous vehicles ) for John Deere. I have worked as a data scientist at companies like Morgan Stanley, and I am also participating in several artificial intelligence related researches with Óbuda University. I am here to share the most cutting edge technologies surrounding machine learning and AWS.

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