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Free Download Udemy - AWS Certified AI Practitioner (AIF-C01) By Chad Smith Released 3/2025 By Chad Smith MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 5h 43m | Size: 1.51 GB Table of contents Introduction AWS Certified AI Practitioner (AIF-C01): Introduction Module 1: Exam Foundation Module Introduction Lesson 1: Exam Guide Learning objectives 1.1 Introduction 1.2 Target Candidate Description 1.3 Exam Content 1.4 Exam Question Domains Module 2: Fundamentals of AI and ML Module Introduction Lesson 2: Basic AI Concepts Learning objectives 2.1 Basic AI Terminology 2.2 Introduction to Machine Learning 2.3 Introduction to Deep Learning 2.4 Question Breakdown 1 2.5 Question Breakdown 2 Lesson 3: Practical Use Cases For AI Learning objectives 3.1 AI Patterns and Anti-patterns 3.2 ML Techniques 3.3 Real-world AI Applications 3.4 AWS Managed AI/ML Services 3.5 Question Breakdown 1 3.6 Question Breakdown 2 Lesson 4: ML Development Lifecycle Learning objectives 4.1 ML Pipeline Components 4.2 ML Model Sources and Deployment Types 4.3 Introduction to ML Ops 4.4 AWS ML Pipeline Services 4.5 ML Model Performance Metrics 4.6 Question Breakdown 1 4.7 Question Breakdown 2 Module 3: Fundamentals of Generative AI Module Introduction Lesson 5: Basic Concepts of Generative AI Learning objectives 5.1 Basic Generative AI Terminology 5.2 Generative AI Use Cases 5.3 Foundation Model Lifecycle 5.4 Question Breakdown 1 5.5 Question Breakdown 2 Lesson 6: Generative AI Capabilities and Limitations Learning objectives 6.1 Generative AI Advantages 6.2 Generative AI Disadvantages 6.3 Model Selection Decision Tree 6.4 Generative AI Business Value and Metrics 6.5 Question Breakdown 1 6.6 Question Breakdown 2 Lesson 7: AWS Generative AI Offerings Learning objectives 7.1 AWS Generative AI Services and Features 7.2 AWS Generative AI Advantages and Benefits 7.3 AWS Generative AI Cost Tradeoffs 7.4 Question Breakdown 1 7.5 Question Breakdown 2 Module 4: Applications of Foundation Models Module Introduction Lesson 8: Foundation Model Design Learning objectives 8.1 Pre-trained Model Selection Criteria 8.2 Model Inference Parameters 8.3 Introduction to RAG 8.4 Introduction to Vector Databases 8.5 AWS Vector Database Service 8.6 Foundation Model Customization Cost Tradeoffs 8.7 Generative AI Agents 8.8 Question Breakdown 1 8.9 Question Breakdown 2 Lesson 9: Foundation Model Performance Learning objectives 9.1 Foundation Model Performance Metrics and Evaluation 9.2 Foundation Model Business Objective Criteria 9.3 Question Breakdown 1 9.4 Question Breakdown 2 Lesson 10: Foundation Model Training and Fine Tuning Learning objectives 10.1 Foundation Model Training 10.2 Foundation Model Fine-tuning 10.3 Foundation Model Data Preparation 10.4 Question Breakdown 1 10.5 Question Breakdown 2 Lesson 11: Prompt Engineering Learning objectives 11.1 Prompt Workflow 11.2 Prompt Engineering Concepts 11.3 Prompt Engineering Techniques 11.4 Prompt Engineering Best Practices 11.5 Prompt Engineering Risks and Limitations 11.6 Question Breakdown 1 11.7 Question Breakdown 2 Module 5: Responsible and Secure AI Solutions Module Introduction Lesson 12: Responsible AI System Development Learning objectives 12.1 Responsible AI Features 12.2 AWS Responsible AI Tools 12.3 Responsible AI Model Selection Practices 12.4 Generative AI Legal Risks 12.5 AI Dataset Characteristics 12.6 AI Bias and Variance 12.7 AWS AI Bias Detection Tools 12.8 Question Breakdown 1 12.9 Question Breakdown 2 Lesson 13: Transparent and Explainable AI Models Learning objectives 13.1 Transparency and Explainability Definitions 13.2 AWS Transparency and Explainability Tools 13.3 AI Model Safety and Transparency Tradeoffs 13.4 Human-centered AI Design Principles 13.5 Question Breakdown 1 13.6 Question Breakdown 2 Lesson 14: AI Security Learning objectives 14.1 AWS AI Security Services and Features 14.2 Data Citations and Origin Documentation 14.3 Secure Data Engineering Best Practices 14.4 AI Security and Privacy Considerations 14.5 Question Breakdown 1 14.6 Question Breakdown 2 Lesson 15: AI Governance and Compliance Learning objectives 15.1 AWS Governance and Compliance Services 15.2 Data Governance Strategies 15.3 Governance Protocols and Compliance Standards 15.4 Question Breakdown 1 15.5 Question Breakdown 2 Summary AWS Certified AI Practitioner (AIF-C01): Summary DOWNLOAD NOW: Udemy - 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Free Download Udemy - Aws Certified Ai Practitioner - Aif-C01 Published: 2/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 4.12 GB | Duration: 7h 58m Prepare yourself for the AWS Certified AI Practitioner certification exam What you'll learn Students will gain a strong foundation knowledge on Machine Learning and Artificial Intelligence. Students will get lots of hands-on view onto using services on AWS for Machine Learning and Artificial Intelligence Students will familiarize with services such as Amazon SageMaker, Bedrock and other services related to the field of Machine Learning and AI Students will gain foundation knowledge when it comes to Generative AI. Students will be better prepared to attempt the AWS Certified AI Practitioner exam. Requirements No prior knowledge is needed on Machine Learning and Artificial Intelligence. We will cover all core concepts in this course. No prior knowledge is needed on AWS. We will learn in the course itself on how to use the services when it comes to Machine Learning and Artificial Intelligence. Description Few words have been spoken more often than 'Generative AI' in today's world. We are witnessing an extraordinary transformation, and it's crucial that we stay prepared and up-to-date with advancements in Artificial Intelligence.The AWS Certified AI Practitioner exam is an excellent starting point. This exam covers the foundational aspects of Machine Learning and AI services offered on AWS, providing a solid foundation for anyone looking to enter the AI field.So what all are we going to cover in this courseFirst and foremost we'll cover the foundational aspects of Machine Learning - We'll learn about the Machine Learning process, how data plays an important role.Then we move into using tools such as Amazon SageMaker Canvas, Data Wrangler to create our Machine Learning model. We'll see how to perform classification and regression from a no-coding aspect.When it comes to Machine Learning, we'll also go through important aspects such as Responsible AI, MLOps, Machine Learning Lifecycle - AWS Well-Architected Framework etc.Then we will move onto learning about the different AWS Managed AI services. This includes the Amazon Comprehend, Amazon Rekognition and other AWS Managed AI services.Then we'll push into learning about Generative AI. We will first have a quick Overview on the different foundation models such as OpenAI GPT, Anthropic Claude etc.Next, we'll move onto using Amazon Bedrock on AWS. Will look into using the foundation models available on Amazon Bedrock. Look at the ever important aspect of Prompt Engineering.Next will dive into Security, Governance and Security. We will understand how services like AWS CloudWatch, AWS CloudTrail and many others can supplement the security aspect of our AI-based applications.Finally we have a Practice Test Section - As part of this course, you will have free access to two practice tests. These will allow you to assess your understanding and gauge how well you've grasped the key concepts covered throughout the course.It's the future and its now. Start your path into the world of Artificial Intelligence. Overview Section 1: Introduction Lecture 1 How has the course been structured Lecture 2 Introduction to Cloud Computing Lecture 3 Using Amazon Web Services as a cloud service Lecture 4 Lab - Creating an AWS Account Lecture 5 Accessing your AWS Account Lecture 6 Our first AWS service - Amazon S3 Lecture 7 Lab - Working with Amazon S3 Lecture 8 Review of Amazon S3 Section 2: Let's work on Machine Learning Lecture 9 Understanding different terms Lecture 10 Considering Machine Learning Lecture 11 Broad-level understanding of the Machine Learning process Lecture 12 Data - The star of the show Lecture 13 Different types of data Lecture 14 Different types of Machine Learning tasks Lecture 15 Amazon SageMaker AI Lecture 16 Quick Intro on different compute options Lecture 17 Lab - Building an EC2 Instance Lecture 18 Lab - Connecting to the EC2 Instance Lecture 19 A note on the costing aspect Lecture 20 Lab - Creating an Amazon SageMaker domain Lecture 21 Quick tour of Amazon SageMaker Studio Lecture 22 Our data set Lecture 23 Lab - Launching SageMaker Canvas Lecture 24 Lab - Amazon Canvas - Data Wrangler - Ingesting our data Lecture 25 Lab - Amazon Canvas - Data Wrangler - Data Insights Lecture 26 Lab - Amazon Canvas - Data Wrangler - Transforming data Lecture 27 Lab - Amazon Canvas - Training the Model Lecture 28 Lab - Amazon Canvas - Making predictions Lecture 29 Amazon Canvas - Analyzing results Lecture 30 Amazon SageMaker feature store Lecture 31 Gotcha's when using training data Lecture 32 Amazon SageMaker - Using the ready-to-use models Lecture 33 Amazon SageMaker Jumpstart Lecture 34 Amazon SageMaker Clarify Lecture 35 Amazon SageMaker Ground Truth Lecture 36 Synthetic data Lecture 37 Different use cases for usage of Machine Learning Lecture 38 Principles of Response AI Lecture 39 Overview on MLOps Lecture 40 Machine Learning Lifecycle - AWS Well-Architected Framework Section 3: AWS Managed AI services Lecture 41 Using the inbuilt AWS AI services Lecture 42 Amazon Comprehend Lecture 43 Lab - Using the Amazon Comprehend service Lecture 44 Amazon Textract Lecture 45 Lab - Using the Amazon Textract service Lecture 46 Amazon Transcribe Lecture 47 Lab - Using Amazon Transcribe Lecture 48 Amazon Rekognition Lecture 49 Lab - Using Amazon Rekognition Lecture 50 Amazon Polly Lecture 51 Lab - Using Amazon Polly Lecture 52 Amazon Translate Lecture 53 Lab - Amazon Translate Lecture 54 Amazon Forecast Lecture 55 Amazon Lex Lecture 56 Lab - Using Amazon Lex Lecture 57 Amazon Personalize Lecture 58 Amazon Comprehend Medical Lecture 59 Amazon Kendra Section 4: Generative AI Lecture 60 Large Language Models Lecture 61 What is a Foundation Model Lecture 62 Introduction to Generative AI Lecture 63 A look at using ChatGPT Lecture 64 Anthropic Claude Lecture 65 Stable Diffusion Lecture 66 Hugging Face Lecture 67 Meta Llama Lecture 68 What is Amazon Bedrock Lecture 69 Lab - Amazon Bedrock - Requesting access to models Lecture 70 Amazon Bedrock - Using Amazon Titan Model Lecture 71 Amazon Bedrock - Using Amazon Titan Image Generator Lecture 72 Amazon Bedrock - Inference parameters Lecture 73 Prompt Engineering Lecture 74 Prompt Engineering - Be clear Lecture 75 Prompt Engineering - Different types of prompts Lecture 76 Prompt Engineering - Using system prompts Lecture 77 Prompt Engineering - Passing data and instructions Lecture 78 Prompt Engineering - Prompt Templates Lecture 79 Prompt Engineering - Resources Lecture 80 When to choose what model Lecture 81 Evaluating Foundation Models Lecture 82 Customizing foundation models Lecture 83 Amazon Q Developer Lecture 84 Lab - Amazon RDS Aurora - Launching an instance Lecture 85 Lab - Amazon RDS Aurora - Connecting to the database Lecture 86 Lab - Amazon RDS Aurora - Connecting to the database - Resources Lecture 87 What is Amazon OpenSearch Lecture 88 What is RAG - Retrieval Augmented Generation Lecture 89 Amazon Bedrock - Knowledge base - Chat with your document Lecture 90 Lab - Amazon Bedrock - Knowledge Base - Implementation Overview Lecture 91 Lab - Amazon Bedrock - Knowledge Base - Creating an IAM user Lecture 92 Lab - Amazon Bedrock - Knowledge Base - Implementation Lecture 93 Challenges on using Generative-AI Lecture 94 Amazon Bedrock Guardrails Lecture 95 Lab - Amazon Bedrock Guardrails Lecture 96 Amazon Bedrock Agents Lecture 97 More on Amazon Bedrock pricing Section 5: Security and Monitoring on AWS Lecture 98 Identity and Access Management Lecture 99 IAM Users and Groups Lecture 100 AWS Key Management service and Amazon Bedrock Lecture 101 What is Amazon CloudWatch Lecture 102 Amazon Bedrock and Amazon CloudWatch Lecture 103 Lab - Amazon Bedrock and Amazon CloudWatch Lecture 104 What is AWS CloudTrail Lecture 105 Amazon Bedrock - AWS PrivateLink Lecture 106 Amazon SageMaker and network isolation Lecture 107 Amazon Macie Lecture 108 AWS Config Lecture 109 AWS Artifact Lecture 110 AWS Audit Manager Lecture 111 AWS Trusted Advisor Lecture 112 Quick note on the design of a conversational chatbot Lecture 113 Securing your Gen-AI applications Lecture 114 Generative AI Security Scoping Matrix Section 6: Practice Tests This course is for students who wants to enter the world of Machine Learning, Artificial Intelligence and Gen-AI. This course will teach students on how to use services on AWS when it comes to Machine Learning, Artificial Intelligence and Gen-AI. This course is meant for students who wants to give the AWS Certified AI Practitioner exam.,This course will teach students on how to use services on AWS when it comes to Machine Learning, Artificial Intelligence and Gen-AI.,This course is meant for students who want to give the AWS Certified AI Practitioner exam. 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Free Download [NEW] AWS Certified AI Practitioner AIF-C01 by Jairo Pirona Published 10/2024 Created by Jairo Pirona | Trainer & Solutions Architect. MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 99 Lectures ( 8h 33m ) | Size: 3.3 GB Pass the AWS AI Practitioner AIF-C01 exam with this course by Jairo Pirona | Practice Exam included | All topics covered What you'll learn: PASS the AWS Certified AI Practitioner Exam (AIF-C01) Master key concepts of AI, machine learning, and generative AI. Identify real-world AI use cases in Amazon Web Services. Understand responsible practices and security in AI solutions. and more... Requirements: Basic computing and cloud skills. Access to an AWS account for hands-on practice. Interest in artificial intelligence and machine learning. Desire to obtain the AWS Certified AI Practitioner certification Description: Discover the future of Artificial Intelligence (AI) and Machine Learning (ML) with AWS. In this course, designed for the AWS Certified AI Practitioner exam, you will learn the fundamentals of artificial intelligence, machine learning, and deep learning, applied through AWS's advanced services. This course is focused on equipping you with the tools needed to understand, implement, and leverage AI solutions in the real world.Throughout the modules, you will explore essential concepts, practical use cases, and best practices for working with advanced technologies like generative AI. Additionally, we will delve into the importance of applying AI responsibly and securely, following industry standards.This is NOT a boring course of voice and PowerPoint lectures. Here I will discuss and present the material in an interactive and engaging style that will keep you interested and make it easier to understand. Check out the free videos available and you will see the difference!What will you learn?Fundamentals of Artificial Intelligence and Machine Learning (ML)You will understand the basics of AI and ML, including neural networks, computer vision, and natural language processing (NLP). We will examine the key differences between artificial intelligence, machine learning, and deep learning, and learn how to identify when it's appropriate to apply these technologies.Generative Artificial IntelligenceYou will discover how generative AI can create new content, such as text, images, and audio, from existing data. We'll see examples of generative models and their practical applications across industries, such as creative content generation, software development, and much more.Foundation Models and Fine-TuningYou will learn about pre-trained models and how to choose the right one for different scenarios. Additionally, you will explore fine-tuning techniques to optimize model performance and how to customize them for specific use cases.Responsible Artificial IntelligenceYou will understand the ethical principles of AI, including transparency, privacy, and bias mitigation. This module will also cover the tools AWS offers to ensure models are secure, explainable, and adhere to responsibility standards.Security, Compliance, and Governance for AI SolutionsYou will learn how to implement governance and security strategies for AI solutions, ensuring systems meet regulatory and best practice standards. This includes handling data securely and protecting models from potential vulnerabilities.Course Contents and Domain DistributionThe course is aligned with the five key domains of the AWS Certified AI Practitioner exam, providing a solid foundation to help you achieve certification. These domains are distributed as follows:Domain 1: Fundamentals of AI and ML (20% of scored content)Domain 2: Fundamentals of Generative AI (24% of scored content)Domain 3: Applications of Foundation Models (28% of scored content)Domain 4: Guidelines for Responsible AI (14% of scored content)Domain 5: Security, Compliance, and Governance for AI Solutions (14% of scored content)Who is this course for?This course is designed for anyone looking to gain a solid understanding of the principles of artificial intelligence and machine learning with AWS. You don't need to be an expert in programming or advanced mathematics; the course covers everything from basic concepts to more advanced applications, all in an accessible way. It is ideal for:Professionals seeking to enter the field of artificial intelligenceDevelopers looking to implement AI solutions on AWSBusiness leaders who want to integrate AI into their projectsCandidates for the AWS Certified AI Practitioner examPrerequisitesNo prior technical knowledge in AI or machine learning is required, but basic familiarity with AWS services and cloud computing concepts will help you get the most out of the course content. Who this course is for: Professionals seeking AWS Certified AI Practitioner certification. AI students interested in AWS cloud. Developers wanting to apply AI in business solutions. Executives looking to understand the value of AI for their business. 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Free Download Aws Certified Ai Practitioner Aif-C01 Exam Preparation Guide Published 9/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1.28 GB | Duration: 3h 3m Your Fast Track to Acing the Certification Exam What you'll learn Understanding of important and essential exam preparation material Concised and summarized study notes Videos containing detailed explanations, advice, and tips Guidance on how to crack the exam Requirements Understanding of AWS services preferred Description AWS Certified AI Practitioner AIF-C01 Exam Preparation Guide is designed to help you efficiently prepare and pass the AWS Certified AI Practitioner exam. It provides a structured approach called the 6 Steps to Success, that ensures comprehensive learning, helps you build the foundational knowledge, and provides you with the right guidance and practical tips to clear the certification exam. There are two possible scenarios:Scenario 1: You are familiar with AWSIf you're already familiar with AWS, have passed the AWS Cloud Practitioner exam, or have previous work experience with AWS, I would suggest you visit the section 8: Refresh your AWS skills. It will help you refresh your foundational AWS concepts.Scenario 2: You are new to AWS If you are new to AWS, you should start your preparations with the study material for AWS Certified Cloud Practitioner exam. It is completely optional if you want to sign up for the AWS Certified Cloud Practitioner certification exam. But the preparation material is important as it will clear the foundational concepts and principles on AWS Cloud. Then, you should enroll in the course on Udemy entitled AWS Solution Architect Associate (SAA-C03): Exam Readiness by Amit Prabhu. My videos and study notes in the course will help you further reinforce the concepts better. Once you are familiar and confident about the AWS services, you can start with this course. AWS Certified AI Practitioner AIF-C01 Exam Preparation Guide is structured around the five domains of the exam, with study notes and videos for each task. My detailed study notes simplify and summarize essential concepts, providing you a good compilation of all the necessary and relevant exam preparation materials. The accompanying videos provide tips, advice, and helps you identify the critical concepts that have a probability of a question being asked around them in the certification exam. Once you complete this course, take sample practice tests available in a separate course entitled Practice Tests: AWS Certified AI Practitioner Exam (AIF-C01). After consistently scoring above 80-85%, you'll be ready to confidently sit for the exam.I am available to support and assist you. Please send me a connection request via LinkedIn. I will do my best to answer your questions and clear your doubts. Good luck with the exam preparation! Overview Section 1: Introduction Lecture 1 Introduction Lecture 2 Sign your coaching contract Section 2: Domain 1: Fundamentals of AI and ML Lecture 3 1.1 Explain basic AI concepts and terminologies Lecture 4 Study Notes 1.1 Explain basic AI concepts and terminologies Lecture 5 1.2 Identify practical use cases for AI. Lecture 6 Study Notes 1.2 Identify practical use cases for AI Lecture 7 1.3 Describe the ML development lifecycle Lecture 8 Study Notes 1.3 Describe the ML development lifecycle Section 3: Domain 2: Fundamentals of Generative AI Lecture 9 2.1 Explain the basic concepts of generative AI Lecture 10 Study Notes 2.1 Explain the basic concepts of generative AI Lecture 11 2.2 Capabilities and limitations of generative AI for solving business problems Lecture 12 Study Notes 2.2 Capabilities & limitations of genAI for solving business problem Lecture 13 2.3 Describe AWS infrastructure and technologies for building generative AI apps Lecture 14 Study Notes 2.3 Describe AWS infra and technologies for building genAI apps Section 4: Domain 3: Applications of Foundation Models Lecture 15 3.1 Design considerations for applications that use foundation models Lecture 16 Study Notes 3.1 Design considerations for apps that use foundation models Lecture 17 3.2 Choose effective prompt engineering techniques Lecture 18 3.3 Describe the training and fine tuning process for foundation models Lecture 19 Study Notes 3.2 Choose effective prompt engineering techniques Lecture 20 Study Notes 3.4 Describe methods to evaluate foundation model performance Lecture 21 Study Notes 3.3 Describe training and finetuning process for foundation models Lecture 22 3.4 Describe methods to evaluate foundation model performance Section 5: Domain 4: Guidelines for Responsible AI Lecture 23 4.1 Explain the development of AI systems that are responsible Lecture 24 Study Notes 4.1 Explain the development of AI systems that are responsible Lecture 25 4.2 Recognize the importance of transparent and explainable models Lecture 26 Study Notes 4.2 Recognize the importance of transparent and explainable models Section 6: Domain 5: Security, Compliance, and Governance for AI Solutions Lecture 27 5.1 Explain methods to secure AI systems Lecture 28 Study Notes 5.1 Explain methods to secure AI systems Lecture 29 5.2 Recognize governance and compliance regulations for AI systems Lecture 30 Study Notes 5.2 Recognize governance and compliance regulations for AI systems Section 7: Important AWS Services Lecture 31 Important AWS Services Section 8: Refresh your AWS Skills Lecture 32 Refresh your AWS Skills Section 9: Conclusion Lecture 33 Conclusion AWS AI Practitioner Certification aspirants Homepage https://www.udemy.com/course/aws-certified-ai-practitioner-aif-exam-preparation-guide_amitprabhu/ TakeFile https://takefile.link/0sptcflya49m/sxwpx.Aws.Certified.Ai.Practitioner.AifC01.Exam.Preparation.Guide.part1.rar.html https://takefile.link/2xxygj2phzbp/sxwpx.Aws.Certified.Ai.Practitioner.AifC01.Exam.Preparation.Guide.part2.rar.html Rapidgator https://rg.to/file/d31ea7af2ae72553ec84bdfb7a8bf4a0/sxwpx.Aws.Certified.Ai.Practitioner.AifC01.Exam.Preparation.Guide.part1.rar.html https://rg.to/file/e86a915738b623049cdb9582809f985f/sxwpx.Aws.Certified.Ai.Practitioner.AifC01.Exam.Preparation.Guide.part2.rar.html Fikper Free Download https://fikper.com/0IKEx0i7Tg/sxwpx.Aws.Certified.Ai.Practitioner.AifC01.Exam.Preparation.Guide.part1.rar.html https://fikper.com/AIQFtic3uG/sxwpx.Aws.Certified.Ai.Practitioner.AifC01.Exam.Preparation.Guide.part2.rar.html No Password - Links are Interchangeable