Ai Ecosystem For The Absolute Beginners - Hands-On

Learn AI Ecosystem (AI, ML, DL, GenAI) with lectures, quizzes, various hands-on demos and exercises

What you'll learn

Introduction to AI Ecosystem - AI, ML, DL, GenAI, Prompt Engineering

AI Lifecycle and Business benefits

AI hands-on using Amazon Rekognition Service

Understanding ML and Learning types

ML hands-on with Amazon Forecast Service

Deep Learning and Neural Networks Fundamentals

DL hands-on with Amazon Comprehend Service

Deep dive into Generative AI, its algorithms and future prospects

GenAI hands-on using Amazon Bedrock Service

Prompt Engineering and best practices

ChatGPT hands-on

Responsible AI

Capstone project using AWS Bedrock

Requirements

Basic Unix/Linux Knowledge

AWS Free Tier Account

Good to have Python Basic Knowledge (Not Mandatory)

No prior experience is required

Description

What's Covered in this Course?The "AI Ecosystem for Absolute Beginners" course is designed to accommodate learners of all levels, from beginners to experienced professionals looking to explore the world of Artificial Intelligence. Acting as a foundational pillar, this course facilitates your journey into the AI ecosystem. Starting with the basics of AI, the course guides you through the lifecycle of AI applications and essential concepts. It also covers the basics of Machine Learning, Deep Learning, and Generative AI, supported by practical hands-on demos using AWS services such as Rekognition, Forecast, Comprehend, and Bedrock. Additionally, it also explores prompt engineering, featuring a comprehensive hands-on demonstration with ChatGPT, concluding with a capstone project focused on Generative AI.Whether you're new to AI or aiming to deepen your understanding, this course is tailored to meet your needs.What is Artificial Intelligence (AI)?Artificial Intelligence (AI) is a revolutionary technology that enables machines to mimic human-like behavior. In today's world, AI powers virtual assistants, autonomous vehicles, and personalised recommendations, transforming industries from healthcare to finance. By analysing large datasets and identifying patterns, AI algorithms continuously improve their performance, driving innovation and reshaping the way we work and live.Course Structure:LecturesDemosQuizzesAssignmentsCourse Contents:Introduction to AI EcosystemGetting Started with Artificial Intelligence (AI)AI Evolution, Business Benefits, Real World Use CasesAmazon Rekognition Service with Hands-on Demo for Label Detection, Facial Analysis and Capstone ProjectUnderstanding Machine Learning (ML) and Real World Use CasesData Preprocessing Techniques, Model Evaluation and ValidationAmazon Forecast Service with Hands-on Demo for Time Series ForecastingGetting Started with Deep Learning (DL) and Artificial Neural Networks (ANN)Amazon Comprehend Service with Hands-on Demo for Sentiment AnalysisGetting started with GenAICore GenAI Algorithms and WorkflowGenAI Application Fields, Future Trends and ToolSetAmazon Bedrock Service with Hands-on Demo for Text Generation, Image Generation and Chatbot)Understanding Prompt EngineeringPrompt Engineering using ChatGPTPotential Risks of AIAI Ethical ConsiderationsBest Practices of AIEnd to End Capstone Project for AI EcosystemAll sections in this course are demonstrated Live, to guide and direct to create your own local environment, perform all exercises and learn by doing!!!

Overview

Section 1: Introduction

Lecture 1 Course Introduction

Lecture 2 Course Handbook - AI Ecosystem for the Absolute Beginners

Lecture 3 GitHub Repository Link

Section 2: Getting started with Artificial Intelligence (AI)

Lecture 4 Introduction to AI, AI Evolution and Business Benefits

Lecture 5 AI Ecosystem

Lecture 6 Real World Use Cases of AI

Lecture 7 Lifecycle of AI

Lecture 8 AWS Cloud Basics for beginners (OPTIONAL)

Lecture 9 Introduction to various AWS AI Services

Lecture 10 Getting Started with Amazon Rekognition and Various Use Cases

Lecture 11 Demo - Amazon Rekognition (Label Detection,Facial Analysis and Capstone Project)

Section 3: Understanding Machine Learning (ML)

Lecture 12 Understanding ML and Learning types

Lecture 13 Data Preprocessing Techniques, Model Evaluation and Validation

Lecture 14 Real World Use Cases of ML

Lecture 15 Getting Started with Amazon Forecast and Various Use Cases

Lecture 16 Demo - Amazon Forecast for Time Series Forecasting

Section 4: Deep Learning (DL) and Artificial Neural Network (ANN) Fundamentals

Lecture 17 Getting Started with Deep Learning (DL) and Artificial Neural Networks (ANN)

Lecture 18 Real world Use Cases of DL

Lecture 19 Understanding Amazon Comprehend Service and Various Use Cases

Lecture 20 Demo - Amazon Comprehend for Sentiment Analysis

Section 5: Understanding Generative AI (GenAI)

Lecture 21 Understanding GenAI and Its Advantages

Lecture 22 Core GenAI Algorithms, Models and Workflow

Lecture 23 Applications Fields and Future Trends

Lecture 24 GenAI Toolset

Lecture 25 Understanding Amazon Bedrock Service, Workflow and Use Cases

Lecture 26 Demo - Amazon Bedrock (Text Generation, Chatbot, Image Generation)

Section 6: Getting Started with Prompt Engineering

Lecture 27 Understanding Prompt Engineering

Lecture 28 Demo - Prompt Engineering using ChatGPT

Section 7: Responsible AI

Lecture 29 Risks, Ethical Considerations and AI Best Practices

AI & ML Engineers,Data Scientists/Data Engineers,Anyone who wants to get started with AI Ecosystem (AI, ML, DL and Generative AI) Journey,Business Professionals and Leaders, Entrepreneurs, CXOs, Business Managers,Aspiring AI/Generative AI Enthusiasts