Overview

This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Unlock the power of Artificial Intelligence (AI) with this beginner-friendly, hands-on course. Dive into the fundamentals of AI and explore its evolution, applications, and business benefits. You'll journey through the key components of the AI ecosystem, from machine learning to deep learning and generative AI. Real-world use cases of AI and ML across industries will provide a practical perspective on their vast potential. Throughout the course, you'll engage with interactive lessons covering AWS Cloud services, Amazon Rekognition, Amazon Forecast, and tools like Amazon Comprehend and Amazon Bedrock. Demonstrations and hands-on exercises allow you to apply your learning in real-time, empowering you to develop AI-driven solutions and use cases. This course is ideal for individuals with little to no experience in AI, machine learning, or cloud computing. It’s structured to take you from basic concepts to real-world applications, making AI more accessible than ever. No prior knowledge is required, and the course ensures you gain valuable practical skills at every step. By the end of the course, you will be able to understand AI's core concepts, use AWS AI services effectively, apply machine learning and deep learning models, and build a hands-on project utilizing AWS Bedrock.

Syllabus

Introduction

In this module, we will introduce you to the course, its goals, and its structure. You’ll get an overview of the content, see how hands-on learning empowers you, and understand how each section of the course builds toward mastering the AI ecosystem.

Getting Started with Artificial Intelligence (AI)

In this module, we will introduce you to the fundamentals of Artificial Intelligence, tracing its evolution and understanding its core components. You’ll explore AI's profound impact on industries through practical use cases, and learn how businesses leverage AI to stay competitive.

Understanding Machine Learning (ML)

In this module, we will dive deep into the principles of Machine Learning, covering its different types and key techniques. You’ll explore how data is processed and how models are evaluated to ensure they perform well in real-world applications.

Deep Learning (DL) and Artificial Neural Network (ANN) Fundamentals

In this module, we will explore the cutting-edge field of Deep Learning, focusing on its foundational concepts and the powerful potential of Artificial Neural Networks. You’ll also get hands-on with Amazon Comprehend to apply DL in sentiment analysis and other NLP tasks.

Understanding Generative AI (GenAI)

In this module, we will introduce you to Generative AI, exploring its unique capabilities and how it is transforming industries like entertainment, technology, and marketing. You’ll learn about the key models behind it and work with Amazon Bedrock for hands-on projects.

Getting Started with Prompt Engineering

In this module, we will introduce the concept of prompt engineering, a crucial skill for improving AI-generated outputs. You’ll also get hands-on practice with ChatGPT and Firebase Studio, applying AI in real-world projects and gaining valuable technical experience.

Responsible AI

In this module, we will explore the ethical dimensions of AI, focusing on the potential risks and the importance of implementing AI responsibly. You’ll learn how to balance innovation with ethical considerations, ensuring that AI solutions align with societal values.

Capstone Project using AWS Bedrock

In this module, we will guide you through a capstone project that allows you to apply your learning to a real-world scenario using AWS Bedrock. This final project will challenge you to integrate multiple AI components and showcase your skills in a comprehensive solution.

Capstone Project for Model Training

In this module, we will focus on training a custom AI model from scratch, using the techniques and tools you've learned. You’ll refine the model’s performance, optimize it, and deploy it as part of your final capstone project, ensuring a robust and scalable AI solution.