Ai Ecosystem For The Absolute Beginners – Hands–On

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

Homepage

https://www.udemy.com/course/ai-ecosystem-for-the-absolute-beginners-hands-on/