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Comprehensive AWS Certified AI Practitioner AIF-C01 Bootcamp
Last updated 9/2026
Created by Vladimir Raykov
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English + subtitle | Duration: 187 Lectures ( 17h 0m ) | Size: 10.3 GB
Master AIF-C01 & Pass on Your First Attempt | 2 Practice Exams + 330 Questions with Detailed Explanations
What you'll learn
Comprehensive Preparation For AWS Certified AI Practitioner (AIF-C01) Certification: 17h High-Quality Video Content + A Total Of 450 Questions & Explanations.[Up-To-Date] Master The AIF-C01 Exam - No Previous Knowledge Needed.[able] Recap Of Key Concepts - PDF file (119 Pages). Explain what an AI agent is, how it uses tools and memory, and when an agent beats plain automation. Identify when to use Amazon Bedrock AgentCore, Strands Agents, and Kiro to build and run agents on AWS. Describe Model Context Protocol (MCP) and how multiple agents divide work between them. Differentiate between Artificial Intelligence, Machine Learning, Deep Learning, and Agentic AI. Understand the foundational principles of Neural Networks. Explore the applications of Computer Vision and Natural Language Processing (NLP). Grasp fundamental AWS services and core concepts. Learn the key steps involved in the Machine Learning process. Identify and understand different data types used in Machine Learning. Distinguish and apply the main types of Machine Learning: Supervised, Unsupervised, Reinforcement, and Semi-Supervised Learning. Understand the concept of Inference in Machine Learning. Explore value-adding applications of Artificial Intelligence. Recognize scenarios where Artificial Intelligence may not be the appropriate solution. Gain practical understanding of Amazon Rekognition for image and video analysis. Learn how to utilize Amazon Transcribe for accurate speech-to-text conversion. Discover the capabilities of Amazon Translate for multilingual text translation. Explore Amazon Comprehend for natural language understanding and insights. Understand how to build conversational interfaces with Amazon Lex. Learn to generate lifelike speech with Amazon Polly. Explore Amazon Personalize for creating personalized recommendations. Learn to extract text and data from documents with Amazon Textract. Explore how to implement human review workflows for machine learning predictions with Amazon Augmented AI (A2I). Gain a comprehensive overview of Amazon SageMaker AI and its key components. Understand the different phases of the Machine Learning Development Lifecycle. Learn the distinction between the ML Development Lifecycle and an ML Pipeline. Grasp the fundamental concepts of MLOps. Discover how AWS SageMaker AI tools map to different stages of the ML Pipeline. Explore model sources and selection strategies within Amazon SageMaker AI. Understand key technical performance metrics for classification problems. Learn essential technical performance metrics for regression problems. Understand the overview and significance of Foundation Models (FMs). Gain insights into the world of Large Language Models (LLMs). Learn about tokens, embeddings, and vectors as fundamental building blocks of language models. Explore the capabilities and applications of Multimodal Models. Discover the principles behind Diffusion Models. Understand the different phases of the Foundation Model Lifecycle. Gain a comprehensive overview of Amazon Bedrock. Understand the purpose and capabilities of Amazon SageMaker JumpStart. Understand important inference parameters like Temperature, Top K, Top P, and Output Length. Grasp the concept of Retrieval Augmented Generation (RAG). Explore how to implement RAG and Knowledge Bases using Amazon Bedrock. Understand the different vector database options for storing embeddings. Learn about Foundation Model customization methods, including cost and implementation considerations. Discover how Amazon Bedrock Agents can help accomplish multi-step tasks. Learn fundamental Prompt Engineering techniques to build a strong foundation. Identify and understand various AI vulnerabilities, including exposure, poisoning, hijacking, and prompt injection. Discover various methods for fine-tuning Foundation Models to specific tasks. Understand the crucial steps involved in preparing data for effective Foundation Model fine-tuning. Understand key evaluation metrics for Foundation Models, including Perplexity, BLEU, ROUGE, BERTScore, Accuracy, and F1-Score. Understand the key concepts of Responsible AI. Learn about the legal and ethical concerns surrounding Generative AI. Understand the concepts of Model Fit, Bias, and Variance (Underfitting and Overfitting). Understand AWS AI Service Cards: what they are, why they are important, and see an example. Explore AWS SageMaker Clarify for detecting and mitigating bias in ML models. Understand AI System Security within the context of the AWS Shared Responsibility Model. Learn about Identity and Access Management (IAM) concepts: Users, Groups, Roles, Policies, and Permissions. Explore AWS Encryption Capabilities for securing data at rest and in transit. Understand network security considerations for AI workloads, including AWS PrivateLink. Understand the concepts of data provenance and lineage. Discover governance protocols and frameworks specifically designed for Generative AI.Requirements
No previous Artificial Intelligence or Cloud Computing knowledge or experience neededDescription
This course contains the use of artificial intelligence.
Welcome. This course takes you from no AI background to exam-ready for the AWS Certified AI Practitioner (AIF-C01) certification.
My name is Vladimir Raykov, and I will be your instructor. I earned the AWS Certified AI Practitioner certification in November 2024 and the AWS Certified Generative AI Developer Professional in December 2025, and I hold the AWS Early Adopter badge for both, awarded to the first 5,000 people worldwide to pass. I hold more than 10 cloud and AI certifications in total, including the Google Cloud Professional Cloud Architect.
I have spent the last 10 years teaching online and have helped more than 200,000 students. Now I am here to help you get certified.
Updated for the latest exam guide
AWS revised the AIF-C01 exam guide, and this course is updated to match it. New lectures cover agentic AI, how AI agents use tools and memory, Model Context Protocol, token-based pricing, context engineering, and grounding techniques that keep model output accurate. The newly in-scope services are covered too: Amazon Bedrock AgentCore, Strands Agents, Kiro, Amazon Quick, and AWS Transform. Questions on services that left the exam scope have been replaced.
By the end of the course, you will be ready to sit the official AWS Certified AI Practitioner exam.
You will have a strong foundation in AI, machine learning, deep learning, and agentic AI, explained simply and clearly. More than 300 slides with diagrams and images support that.
You will understand the AWS AI services the exam tests, including Amazon Bedrock, Amazon Bedrock AgentCore, Amazon SageMaker AI, and pre-trained services such as Comprehend, Rekognition, and Textract.
You will learn how AI is applied in real business scenarios and how to judge when AI is the right choice. And you will be ready for the exam's scenario-based questions, because you work through practical examples all the way through the course.
Course structure
The course has 18 structured sections, aligned with the five exam domains: fundamentals of AI and ML, fundamentals of generative AI, applications of foundation models, guidelines for responsible AI, and security, compliance and governance of AI solutions.
You get more than 160 bite-sized video lessons, around 17 hours in total. Every video is scripted for clear, concise delivery, with no filler and no thinking pauses.
You also get more than 330 practice questions with detailed explanations, included as quizzes at the end of each section, and two full-length mock exams of 65 questions each that mirror the real exam format.
A downloadable PDF summarizes the key takeaways for last-minute revision. The course is updated regularly as AWS services and exam content change.
This course is designed for anyone looking to earn the AWS Certified AI Practitioner (AIF-C01) certification and add it to their professional toolkit. No prior AI or cloud experience required.
Whether you want to understand how AI works in real business settings or you are preparing for your next role, this course will give you the knowledge and the confidence to pass the exam.
It's perfect for
This course is for anyone looking to earn the AWS Certified AI Practitioner (AIF-C01) certification. No prior AI or cloud experience is required. It suits business analysts, IT support professionals, marketing professionals, product managers, project managers, team leads, IT managers, sales professionals, and anyone curious about AI and AWS.
By the end, you will not only be prepared to pass the exam. You will understand the concepts behind it.
Ready to get started?
Watch the preview videos, especially "Roadmap to Success", to see my strategy for helping you pass the exam and truly understand the material.
Click enroll, and let's start your AWS AI journey together.
See you inside!
This course is not affiliated with, endorsed by, or sponsored by Amazon Web Services (AWS) or Google Cloud Platform (GCP). AWS and Google Cloud are trademarks of their respective owners. All logos and trademarks are used for educational and identification purposes only.
Who this course is for
Students who want to obtain the AWS Certified AI Practitioner Certification IT professionals Business Analysts Product and Project managers Product Owners and Scrum Masters IT support professionals Marketing and sales professionalsHomepage
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