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

Overview

Unlock 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 learn

Foundational 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

Homepage:

https://www.udemy.com/course/get-aws-ai-certified-handsonquiz-testszero-to-hero-2025/