AWS Tools and Services for AI

AWS Tools and Services for AI

This course is part of AWS AI Practitioner Specialization

Instructor: LearnKartS

Included with Coursera Plus

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2 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

9 hours to complete

3 weeks at 3 hours a week

Flexible schedule

Learn at your own pace

2 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

9 hours to complete

3 weeks at 3 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Understand the fundamentals of Generative AI, including diffusion models, transformer-based LLMs, and multi-modal models.
Learn Retrieval-Augmented Generation (RAG) techniques and fine-tune models with AWS tools for improved AI performance.
Explore Amazon Bedrock, learning to implement Generative AI solutions with advanced language models and prompt engineering techniques.

Details to know

Shareable certificate

Add to your LinkedIn profile

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

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Build your subject-matter expertise

This course is part of the AWS AI Practitioner Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV

Share it on social media and in your performance review

There are 2 modules in this course

Welcome to the course : AWS Tools and Services for AI

This course is designed to equip you with hands-on skills in using AWS AI services and tools to build, deploy, and optimize AI applications. Whether you are an AI enthusiast, developer, or data scientist, this course provides a good grounding in AI technologies, from generative AI to advanced model fine-tuning. This course is the second course of the 3 courses specialization - AWS Certified AI Practitioner. In this course, you'll explore Amazon Bedrock, understand Large Language Models (LLMs), and master prompt engineering techniques to optimize AI interactions. Dive into Retrieval-Augmented Generation (RAG), AWS AI-managed services like Amazon Polly, Comprehend, Transcribe and many more. You'll also gain practical experience with AWS tools for model training, evaluation, and deployment, including Amazon Q and Bedrock. We will learn Prompts, Prompt Engineering and how to adjust hyperparameters to get desired results in Gen-AI. This course will effectively guide you to use various AWS services for AI and Gen-AI. Enroll now to: • Master AWS AI services like Amazon Bedrock, Transcribe, Amazon Q, Lex, Comprehend, Polly and many more. • Explore Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and prompt engineering. • Gain hands-on experience with AWS-managed AI services through hands-on demos

This module introduces the core principles of Generative AI, covering foundational concepts, language models, and prompt engineering. Learners also explore practical applications using Amazon Bedrock and Amazon Q.

What's included

29 videos6 readings7 assignments

29 videosTotal 101 minutes

Welcome to the Course4 minutesPreview module
Learning Objectives0 minutes
Fundamentals of Generative AI 5 minutes
Diffusion Models2 minutes
Transformer-Based Large Language Models (LLMs)2 minutes
Multi-modal Models1 minute
Key Features of Amazon Bedrock5 minutes
Amazon Bedrock – Use Cases1 minute
Demo- Bedrock overview5 minutes
Understanding GPT2 minutes
Implementing Generative AI with Amazon Bedrock4 minutes
Learning Objectives0 minutes
Key Concepts in Language Models: Part-15 minutes
Key Concepts in Language Models: Part-24 minutes
Prompts and Prompt Engineering2 minutes
Designing a Prompt4 minutes
Hyperparameter2 minutes
Choosing Top-p, Top-k and Temperature6 minutes
Prompt Engineering Techniques4 minutes
Demo- Prompt Engineering Techniques5 minutes
Prompt Engineering Risks2 minutes
Prompt Templates1 minute
Demo-Prompt Optimization Parameters6 minutes
Generative AI Foundation Models2 minutes
Practical Applications of Generative AI2 minutes
Amazon Q1 minute
Key Components of Amazon Q1 minute
Developer Fundamentals on Amazon Q2 minutes
Demo- Amazon Q Walkthorugh7 minutes

6 readingsTotal 65 minutes

Course Introduction15 minutes
Bedrock Cost Considerations10 minutes
Amazon Bedrock Agents10 minutes
Gen AI: Measuring Business Efficiency and Value10 minutes
Optimizing Prompts10 minutes
Party Rock - Playground for Gen AI apps10 minutes

7 assignmentsTotal 120 minutes

Core Concepts of Generative AI and Amazon Bedrock15 minutes
Language Models, Prompt Engineering, and Amazon Q30 minutes
Core Concepts of Generative AI15 minutes
Amazon Bedrock15 minutes
Language Models and Prompt Engineering15 minutes
Prompt Engineering Techniques15 minutes
Generative AI Foundation Models and Amazon Q15 minutes

This module explores how Retrieval-Augmented Generation (RAG) enhances AI responses with relevant data and how to optimize AI models for performance and efficiency using AWS AI services.

What's included

21 videos5 readings5 assignments

21 videosTotal 101 minutes

Learning Objectives0 minutesPreview module
RAG (Retrieval-Augmented Generation)4 minutes
Applications of RAG1 minute
RAG – Advantages and Disadvantages4 minutes
AWS AI Managed Services Part-15 minutes
Demo- Amazon Transcribe in Action4 minutes
Demo- Amazon Translate Walkthrough7 minutes
Demo-Simplifying Text Analysis with Comprehend7 minutes
Demo- Exploring Amazon Polly5 minutes
AWS AI Managed Services Part-24 minutes
Demo- understanding Amazon Lex9 minutes
Demo-Amazon Rekognition Walkthrough6 minutes
Demo- Amazon Textract Overview4 minutes
AWS Database Options for Storing Embeddings5 minutes
Learning Objectives0 minutes
Model Pre-Training and Fine-Tuning with AWS 5 minutes
Fine-Tuning for Conversational AI2 minutes
Demo- Fine-Tuning Bedrock Model8 minutes
Model Evaluation Techniques4 minutes
Evaluate and Refine Models Post-deployment5 minutes
Course Completion2 minutes

5 readingsTotal 50 minutes

Amazon Mechanical Turk10 minutes
Amazon Personalize10 minutes
Industry-Specific Use Cases for Model Evaluation10 minutes
Advanced Guidelines for Continuous Model Optimization10 minutes
Summary10 minutes

5 assignmentsTotal 105 minutes

Retrieval-Augmented Generation (RAG) and AWS AI Services30 minutes
Model Optimization30 minutes
Retrieval-Augmented Generation (RAG)15 minutes
AWS AI Managed Services15 minutes
Model Optimization15 minutes

Instructor

LearnKartS

72 Courses66,516 learners

Offered by

LearnKartS

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Frequently asked questions

The course covers Amazon Bedrock for creating generative AI apps, Amazon Q , and AWS AI Managed Services - Transcribe, Translate, Comprehend, Polly, Lex, Rekognition and Textract.

Yes, a course completion certificate is allocated upon completing all graded assignments and quizzes present in the Introduction to AWS course.

Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

AWS Tools and Services for AI

What you'll learn

Details to know

See how employees at top companies are mastering in-demand skills

Build your subject-matter expertise

Earn a career certificate

There are 2 modules in this course

Fundamentals of Generative AI

What's included

29 videosTotal 101 minutes

6 readingsTotal 65 minutes

7 assignmentsTotal 120 minutes

RAG (Retrieval-Augmented Generation) and Optimizing AI Model

What's included

21 videosTotal 101 minutes

5 readingsTotal 50 minutes

5 assignmentsTotal 105 minutes

Instructor

Offered by

Explore more from Cloud Computing

Introduction to AI and Machine Learning

Responsible AI with AWS Security and Governance

Why people choose Coursera for their career

New to Cloud Computing? Start here.

Open new doors with Coursera Plus

Advance your career with an online degree

Join over 3,400 global companies that choose Coursera for Business

Frequently asked questions

More questions

AWS Tools and Services for AI

What you'll learn

Details to know

See how employees at top companies are mastering in-demand skills

Build your subject-matter expertise

Earn a career certificate

There are 2 modules in this course

Fundamentals of Generative AI

What's included

RAG (Retrieval-Augmented Generation) and Optimizing AI Model

What's included

Instructor

Offered by

Explore more from Cloud Computing

Introduction to AI and Machine Learning

Responsible AI with AWS Security and Governance

Why people choose Coursera for their career

New to Cloud Computing? Start here.

Open new doors with Coursera Plus

Advance your career with an online degree

Join over 3,400 global companies that choose Coursera for Business

Frequently asked questions

What are key AWS AI tools and services covered in the course?

Is a certificate provided upon completion of the course?

When will I have access to the lectures and assignments?

More questions