Get Aws Ai Certified: Handson,Quiz & Tests|Zero-To-Hero 2025

Full Certification Prep with Practice Test curated with Amazon Team | Crack your First AWS AI Certification in one shot.

What you'll learn

Master the fundamentals of generative AI and its business applications

Navigate the Amazon Bedrock console with confidence

Pass the AWS Certified AI Practitioner Certification AIF-C01

Learn Prompt Engineering

Learn the key AWS AI services, including a deep dive on Bedrock, Amazon Q and SageMaker

Practice Exam with Explanations included!

Master Amazon Q Developer setup and integration

Create custom models with AI using simple text prompts

Develop effective code generation skills using AI

Optimize code performance with Amazon Q insights

Improve collaborative development workflows

Complete hands-on, real-world AI projects using Amazon Bedrock

Requirements

No AWS Cloud experience is necessary

An AWS account

Hands-On Learning: Hands-on labs and exercises are provided throughout the course to reinforce learning and allow you to practice what you've learned in a real-world environment.

No IT pre-requisites is necessary

No AI pre-requisites is necessary

Enthusiasm to learn about AI and its practical applications

From Basics to Details: We start from the fundamentals of AI/ GenAI/ AWS / Amazon Q, explaining core concepts and terminology in a clear and concise manner.

Description

"AWS AI Practitioner Certification: From Fundamentals to Certification Success"Course OverviewUnlock the power of artificial intelligence in cloud computing with this comprehensive, hands-on course designed to prepare you for the AWS AI Practitioner Certification. Whether you're a technology professional, developer, or aspiring cloud AI specialist, this course provides the knowledge, skills, and practical experience you need to excel.What You'll LearnFoundational AI and Machine Learning ConceptsUnderstand core AI and machine learning principlesExplore the AWS AI/ML technology landscapeLearn how AI technologies integrate with cloud infrastructureGain insights into real-world AI applications and use casesAWS AI Services Deep DiveComprehensive coverage of key AWS AI services:Amazon Bedrock for GenAI ModelAmazon Q Business for BotsAmazon Q Developer for CodingAmazon SageMaker for machine learning model developmentAmazon Rekognition for image and video analysisAmazon Comprehend for natural language processingAmazon Translate and TranscribeAmazon Lex for conversational interfacesAmazon Polly for text-to-speech technologiesHands-On Practical Training30+ hands-on and real-world scenariosStep-by-step demonstrations of AI service configurationsPractical exercises simulating enterprise AI implementationsExam Preparation StrategiesDetailed exam blueprint breakdownComprehensive practice question bank (150+ questions)Multiple full-length mock examsWho Should EnrollCloud professionals looking to specialize in AIDevelopers interested in AI service implementationIT professionals seeking AWS certificationStudents and career changers in technologyAnyone wanting to understand AI's role in cloud computingEnroll now and transform your career with AWS AI expertise!

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 Official AWS Mock Exam

Section 2: Cloud Basics

Lecture 3 Cloud Computing & its Benefits

Lecture 4 Cloud Computing Models

Lecture 5 AWS Infrastructure

Lecture 6 Key Terminologies

Lecture 7 AWS UI Tour

Lecture 8 Setting a Budget

Lecture 9 IAM Users and Roles

Lecture 10 Root User vs IAM User

Lecture 11 IAM Policy

Lecture 12 AWS EC2

Lecture 13 AWS Lambda

Lecture 14 AWS S3

Lecture 15 Amazon VPC

Lecture 16 VPC through Real World Scenario

Lecture 17 Amazon VPC HandsOn

Lecture 18 Connect With Me!!

Section 3: Concepts of AI & ML - Part 1

Lecture 19 What is AI?

Lecture 20 AI, GenAI, ML, Deep Learning Relation

Lecture 21 AI Lifecycle

Lecture 22 What is Generative AI?

Lecture 23 Opportunities available in GenAI

Lecture 24 PartyRock - Experience GenAI with No Experience

Lecture 25 Limitations of GenAI

Lecture 26 GenAI Techniques & Models

Lecture 27 FM vs LLM

Lecture 28 Understanding NLP

Section 4: Amazon Bedrock - With Detailed HandsOn

Lecture 29 Introduction to Bedrock

Lecture 30 Understanding UI

Lecture 31 Enabling Model Access

Lecture 32 Using Chat Playground

Lecture 33 Using Text Playground

Lecture 34 Using Image Playground

Lecture 35 Inference Parameters

Lecture 36 Temperature Hands-On

Lecture 37 Top P Hands-On

Lecture 38 Top K Hands-On

Lecture 39 Most Probable Solution with Parameters

Lecture 40 Additional Configurations

Lecture 41 Fine-Tuning of Models

Lecture 42 Understanding Safeguards

Lecture 43 Guardrails SetUp

Lecture 44 Using Guardrails

Lecture 45 Understanding Builder Tools

Lecture 46 Prompt Management

Lecture 47 Building Knowledge Base - RAG Process

Lecture 48 Crawling & Indexing

Lecture 49 Embedding

Lecture 50 Understanding RAG

Lecture 51 Knowledge Base - Using Root User

Lecture 52 Knowledge Base - Using IAM User

Lecture 53 Understanding Agents

Lecture 54 Agents Walkthrough

Lecture 55 Creating Agents using Assistant

Lecture 56 Understanding Prompt Flow

Lecture 57 Understanding Bedrock Studio

Lecture 58 Criteria for choosing right FM

Lecture 59 Model Evaluation HandsOn

Section 5: Prompt Engineering

Lecture 60 Understanding Prompt Engineering

Lecture 61 Prompt Elements & Techniques

Lecture 62 Zero-Shot Technique + HandsOn

Lecture 63 Few-Shot Technique + HandsOn

Lecture 64 Chain-of-Thoughts Technique + HandsOn

Lecture 65 Modifying Response with Prompts in Bedrock

Lecture 66 Addressing Prompt Issues

Lecture 67 Mitigating Bias

Section 6: Amazon Q Business & Developer - with Detailed HandsOn

Lecture 68 Understanding Q

Lecture 69 Amazon Q UI tour

Lecture 70 Understanding Q Business

Lecture 71 Workflow of Amazon Q Business

Lecture 72 IAM Organisation - For adding Users in Q Business

Lecture 73 IAM Organisation Hands-On

Lecture 74 IAM Identity Center

Lecture 75 Enabling Identity Center - Option 1

Lecture 76 Enabling Identity Center - Option 2

Lecture 77 Adding Users in Identity Center

Lecture 78 Enabling Users in Identity Center

Lecture 79 Adding Permissions to Users

Lecture 80 Q Business Hands-On

Lecture 81 Adding Users in Q Business Hands-On

Lecture 82 Understanding Subscription

Lecture 83 What is Retriever?

Lecture 84 Retriever Settings Hands-On

Lecture 85 Understanding Data Sources

Lecture 86 Data Source - Upload File Hands-On

Lecture 87 Can we Restrict Information?

Lecture 88 Blocking Words - Hands-On

Lecture 89 Apps in Q Business

Lecture 90 Building Apps Hands-On

Lecture 91 Understanding Q Developer

Lecture 92 Understanding Q Developer usage in Console

Lecture 93 Chatting with Amazon Q Developer

Lecture 94 Diagnosing with Amazon Q Developer

Lecture 95 Creating a ticket with Amazon Q Developer

Lecture 96 Can we ask general questions?

Lecture 97 Can we ask for code directly in Lambda?

Lecture 98 Understanding AWS Chatbot

Lecture 99 Utilising AWS Chatbot

Lecture 100 Using Amazon Q with Lambda & Bedrock

Section 7: Basics Concepts of AI & ML - Part 2

Lecture 101 Understanding Machine Learning

Lecture 102 Types of Data

Lecture 103 Understanding ML Development Lifecycle

Lecture 104 Learning Techniques

Lecture 105 Supervised Learning

Lecture 106 Examples of Supervised Learning

Lecture 107 Unsupervised Learning

Lecture 108 Reinforcement Learning

Lecture 109 Human involvement in AI development - RLHF

Lecture 110 HyperParameters

Lecture 111 Model Evaluations Metrics

Lecture 112 GenAI Model Performance Metrics

Lecture 113 Deep Learning

Lecture 114 Understanding MLOps

Section 8: SageMaker - with Detailed HandsOn

Lecture 115 Understanding SageMaker

Lecture 116 SageMaker UI Tour

Lecture 117 SageMaker Services

Lecture 118 All about Data with SageMaker

Lecture 119 Data Wrangler HandsOn

Lecture 120 SageMaker Model Building

Lecture 121 SageMaker Jupyter HandsOn

Lecture 122 SageMaker AutoPilot HandsOn

Lecture 123 SageMaker Canvas HandsOn

Lecture 124 SageMaker JumpStart HandsOn

Lecture 125 SageMaker Training Models

Lecture 126 SageMaker Experiments HandsOn

Lecture 127 SageMaker Deployment

Lecture 128 SageMaker Endpoints HandsOn

Lecture 129 SageMaker Monitoring

Lecture 130 SageMaker Clarify HandsOn

Lecture 131 SageMaker Governance

Lecture 132 SageMaker Model Cards HandsOn

Lecture 133 SageMaker Model Inference for Predictions

Section 9: Other AI Major Services

Lecture 134 Amazon Comprehend

Lecture 135 Amazon OpenSearch

Lecture 136 Amazon QuickSight Q

Lecture 137 Amazon Translate

Lecture 138 Amazon Transcribe

Lecture 139 Amazon Polly

Lecture 140 Amazon Lex

Lecture 141 Amazon Rekognition

Lecture 142 Amazon Forecast (Available in Sagemaker Canvas)

Lecture 143 Amazon Personlize

Lecture 144 Amazon Textract

Lecture 145 Amazon Kendra

Lecture 146 Amazon Augmented AI

Lecture 147 AWS Fraud Detector

Lecture 148 Amazon DeepRacer

Lecture 149 Tranium & Inferentia

Section 10: AI Responsibility, Compliance & Governance

Lecture 150 Responsible AI

Lecture 151 Troubleshooting Challenges in AI - Fit, Bias & Variance

Lecture 152 Responsible Practices for Model Selections

Lecture 153 GenAI Risks

Lecture 154 Importance of Model Transparency

Lecture 155 Tools for Model Transparency

Lecture 156 Data Governance

Lecture 157 Emerging AI Standards

Lecture 158 AWS Artifact

Lecture 159 AWS Audit Manager

Lecture 160 AWS Glue DataBrew for Data Governance

Lecture 161 AWS Lake Formation for Data Governance

Lecture 162 Steps to implement AI Governance strategy

Section 11: AWS AI Security

Lecture 163 AWS Shared Responsibility Model

Lecture 164 IAM Security

Lecture 165 AWS CloudTrail

Lecture 166 AWS KMS

Lecture 167 AWS Macie

Lecture 168 VPC Security with Endpoints

Lecture 169 AWS Inspector

Lecture 170 AWS Trusted Advisor

Lecture 171 AWS Config

Lecture 172 WAF & Shield

Lecture 173 AWS X-Ray

Lecture 174 AWS GuardDuty

Lecture 175 AWS CloudWatch

Lecture 176 Model Vulnerabilities

Lecture 177 Version Control

Section 12: Real Exam Scenario Based Questions

Section 13: Additional content - Take AWS Retake by 2025

Lecture 178 Official AWS Retake till Feb 2025 Coupon Code

Lecture 179 Official Curriculum with AWS Website

Anyone wanting to acquire the knowledge to pass the AWS Certified AI Practitioner Certification,For Beginners: Individuals with little to no experience in AI/ GenAI/ AWS / Amazon Q. Fresh graduates or students looking to kickstart their careers in AI/ GenAI/ AWS / Amazon Q or software development.,Everyone can pick up this course, at their own pace.,For Intermediate Users: Professionals who have some familiarity with AI but want to deepen their understanding and skills. Developers or sysadmins who have worked with AI in basic capacities but seek to expand their knowledge and capabilities.,For Advanced Users: Experienced AI engineers, software architects, or team leads who want to refine their AI skills and stay updated with the latest best practices.,For Career Changers: Individuals transitioning from other IT roles (such as system administration, software development, or quality assurance) to AI / GenAI / Amazon Q