Amazon Nova: Hands-On Learning

Understand capabilities of Amazon Nova models through hands-on experience—without getting lost in technical jargon

What you'll learn

Understand Amazon Nova's Capabilities

Apply Nova Models to Real-World Use Cases

Develop Hands-On Experience with Nova

Master Best Practices for Prompt Engineering

Requirements

Basic understanding of AWS and Generative AI

Description

Welcome to the most engaging and beginner-friendly Amazon Nova digital training! This course is designed for those who want to truly understand capabilities of Amazon Nova models through hands-on experience—without getting lost in technical jargon.Simplified explanationsInstead of overwhelming you with complexity I break down everything down using relatable analogies that make learning intuitive and fun.Learn by doingEach module is packed with hands-on workshops, where you’ll deploy and fine-tune Nova models in real-world scenarios.Real-life usecasesFrom automating customer support to predicting trends, discover how Amazon Nova can transform businesses.Instead of overwhelming you with complex equations and AI terminology, we break everything down using relatable analogies, real-world examples, and simplified explanations that make learning intuitive and fun.Here’s the set of learning objectives for your Amazon Nova Training:Understand Amazon Nova's Capabilities – Gain a clear understanding of what Amazon Nova models are, how they function, and their core capabilities through simplified explanations and relatable analogies.Apply Nova Models to Real-World Use Cases – Learn how to use Amazon Nova for practical business applications, such as automating customer support, trend prediction, and optimizing workflows.Develop Hands-On Experience with Nova – Deploy, fine-tune, and experiment with Amazon Nova models in hands-on workshops, ensuring you can confidently apply what you’ve learned in real-world scenarios.Master Best Practices for Prompt Engineering – Learn how to craft effective prompts to get the most accurate, efficient, and relevant responses from Amazon Nova models, improving their performance for various applications.

Overview

Section 1: Introduction

Lecture 1 Introduction

Section 2: Amazon Nova

Lecture 2 01 - What is Amazon Nova

Lecture 3 02 - Amazon Nova Family

Lecture 4 03 - Quick Comparision

Lecture 5 04 - Amazon Bedrock

Section 3: Hands-on Workshop - 1

Lecture 6 05 - Intro to Workshop

Lecture 7 06 - SageMaker Domain

Lecture 8 07 - JupyterLab Space Setup

Lecture 9 08 - Another Notebook

Section 4: Amazon Nova Canvas

Lecture 10 09 - Text to Image

Lecture 11 10 - Inpainting

Lecture 12 11 - Outpainting

Lecture 13 12 - Background Removal

Lecture 14 13 - Image Variation

Lecture 15 14 - Image Conditioning

Lecture 16 15 - Color Conditioning

Lecture 17 16 - Another workshop

Lecture 18 17 - Cleanup

Section 5: Amazon Nova Reel

Lecture 19 18 - Amazon Nova Reel

Lecture 20 19 - Text to Video

Lecture 21 20 - Image to Video

Lecture 22 21- Prompting Best Practices

Lecture 23 22 - Pricing Information

Section 6: Amazon Nova - Micro, Lite, Pro

Lecture 24 23 - Content Understanding Models

Lecture 25 24 - Some Examples

Lecture 26 25 - Which model to use

Section 7: Prompt Engineering Techniques

Lecture 27 26 - Customizing Foundation Models

Lecture 28 27 - Prompt Engg Part - 1

Lecture 29 28 - Prompt Engg Part - 2

Lecture 30 29 - Prompt Engg Part - 3

Lecture 31 30 - Prompt Engg Part - 4

Section 8: How Amazon Nova is created?

Lecture 32 31 - How a model is created

Lecture 33 32 - Training Infrastructure of Amazon Nova

Section 9: Hands-on Workshop - 2

Lecture 34 33 - Important APIs

Lecture 35 34 - Workshop Setup

Lecture 36 35 - Workshop - Part 1

Lecture 37 36 - Workshop - Part 2

Section 10: What's next?

Lecture 38 37 - Next step and Resources

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