Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
15 Hour(s) 26 Minute(s)
Language
English
Taught by
Vladimir Raykov
Certificate
- Available
- *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Rating
Course Overview
Master AIF-C01 & Pass on Your First Attempt | 2 Practice Exams + 320 Questions with Detailed Explanations
Welcome to the Comprehensive AWS Certified AI Practitioner AIF-C01 Bootcamp — your complete guide to passing the exam.
My name is Vladimir Raykov, and I’ll be your instructor. I’m a Certified AI Practitioner, Project Management Professional, Scrum Master, and Product Owner. I currently work as an Agile Product Manager in a software development company.
I’ve spent the last 10 years teaching online and have helped thousands of students earn their certifications. Now, I’m here to help you do the same.
By the end of the course, you will:
Be well-prepared to take the official AWS Certified AI Practitioner exam (AIF-C01).
Have a strong foundation in core AI, ML, and deep learning concepts — explained simply and clearly - And I’ve created over 300 slides with diagrams and images to make sure that really is the case.
Gain a deep understanding of AI-related AWS services like Amazon Bedrock, Amazon SageMaker AI, and pre-trained services such as Comprehend, Rekognition, and many more.
Learn how AI is applied in real-world business scenarios and how to evaluate when and how to use AI responsibly.
Be ready for the exam’s scenario-based questions by applying what you’ve learned to practical examples throughout the course.
As for the structure of the course, you will find:
18 structured sections, aligned with the 5 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
Over 150 bite-sized video lessons (approx. 15 hours total). Every video is scripted to ensure clear, concise delivery — no filler, no “umm” moments
320+ practice questions with detailed explanations, included as quizzes at the end of each section
2 full-length mock exams, each with 65 questions that mirror the real exam format
A downloadable 119-page PDF summary of key takeaways — perfect for last-minute revision
Real-world AI scenarios to help you connect concepts to practical business use cases
Regular updates based on the latest changes in AWS services and exam content
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're aiming to understand how AI works in real-world business settings or preparing for your next role, this course will give you the knowledge and confidence to pass the exam.
It's perfect for:
Business analysts and IT support professionals
Marketing professionals and product managers
Project managers, Product Owners, and Scrum Masters
IT managers, sales professionals, and anyone curious about AI and AWS
By the end, you’ll not only be prepared to pass the exam — you'll 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!
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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.
This course contains the use of artificial intelligence.
Course Content
- 18 section(s)
- 167 lecture(s)
- Section 1 Course Introduction
- Section 2 Mastering the Basics: AI & ML Concepts
- Section 3 AWS AI Managed Services Deep Dive
- Section 4 Amazon SageMaker AI Essentials And The ML Development Lifecycle
- Section 5 Navigating Generative AI: Core Components, Model Types and Lifecycle
- Section 6 Business Applications of Generative AI
- Section 7 Your GenAI Toolkit: Essential AWS Services and Features
- Section 8 Applications of Foundation Models: Key Design Considerations
- Section 9 Prompt Engineering Essentials and AI Vulnerabilities
- Section 10 Fine-Tuning Foundation Models (FMs) - Deep Dive
- Section 11 Evaluating Foundation Models: Methods and Metrics
- Section 12 Responsible AI Development: Key Concepts And Considerations
- Section 13 Making AI Understandable
- Section 14 Essential Security Practices and Tools on AWS
- Section 15 Data Security and Governance for AI Systems
- Section 16 AI Security, Compliance, and Governance
- Section 17 Practice Exams
- Section 18 Exam Tips & Final Words
What You’ll Learn
- Comprehensive Preparation For AWS Certified AI Practitioner (AIF-C01) Certification: 15h High-Quality Video Content + A Total Of 450 Questions & Explanations.
- [Up-To-Date] Master The AIF-C01 Exam - No Previous Knowledge Needed.
- [Downloadable] Recap Of Key Concepts - PDF file (119 Pages).
- Differentiate between Artificial Intelligence, Machine Learning, and Deep Learning.
- 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.
- Discover how to leverage Amazon Fraud Detector to identify potential fraud.
- Explore Amazon Personalize for creating personalized recommendations.
- Understand how to use Amazon Kendra for intelligent search over documents.
- Learn to extract text and data from documents with Amazon Textract.
- Learn how to leverage Amazon Forecast for time-series forecasting.
- Understand the fundamentals of Amazon Mechanical Turk (MTurk) for crowdsourcing tasks.
- 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.
- Explore Amazon Q Business and Amazon Q Developer for generative AI applications.
- 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.
Skills covered in this course
Reviews
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KKyle Phimvilayphone
the video and outlines of the teaching is cleared.
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AArlene Batada
Amazing explanation of all topics by the instructor. Probably the best one out there for this certification!
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NNaveen J
Thanks for awesome teaching and passion, got certified, Appreciate your help and support
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DDuran Silvana
I have passed the exam yesterday, due to this great course. Vlad's courses are the best structured courses I have taken on Udemy regarding cloud and agile topics. I have passed 3 exams in about 2 weeks due to his great support. I can't recommend him highly enough.
